Discover how Augmentir’s AI transforms the connected worker journey—boosting training, productivity, and continuous improvement across operations.
As AI agents become more deeply embedded in business operations, they carry tremendous potential—but also significant responsibility. At Augmentir, we believe that trust, accountability, and safety must form the foundation of every AI deployment. That’s why we developed our 6 Laws of AI Agents: guiding principles that ensure AI systems operate transparently, responsibly, and safely in real-world environments. These laws are designed not only to safeguard organizations and individuals, but also to help businesses realize the true value of AI without compromising integrity or safety.
All agent activities must be observable. This includes what instructions were given, which tools were used, and what outcomes were produced. Transparency ensures traceability, making it clear how and why decisions were made.
✔Summary: AI must never be a “black box.” Clear visibility builds trust and accountability.
2. Clear Ownership
Every AI agent must have a clearly defined human or organizational owner responsible for its decisions and actions. This ownership must be explicitly documented to prevent ambiguity and ensure accountability at all times.
✔Summary: AI is powerful, but responsibility always rests with people, not machines.
3. AI Origin Disclosure
Whenever an agent provides an answer, recommendation, or decision, it must clearly state that it was generated by AI—and acknowledge that AI can make mistakes. This sets proper expectations and reinforces responsible use.
✔Summary: Clear disclosure prevents overreliance on AI and keeps human judgment central.
4. Persistent AI Disclosure
If an agent’s AI-generated recommendation or content is shared outside its native system (e.g., posted in Microsoft Teams or another platform), the AI origin and disclaimer must remain attached. Transparency should travel with the content wherever the information is shared.
✔Summary: AI-origin labels must stay attached, ensuring clarity across platforms.
5. Human-in-the-Loop for Impactful Actions
Any action that creates, modifies, or deletes a data item that could affect operational outcomes must require human review and approval before completion. For example, a safety report notes oil on a walkway. If an agent attempts to close the issue without cleanup, a human must approve before closure.
✔Summary: AI can recommend actions, but humans must approve decisions with real-world consequences.
6. No GenAI for Life-Critical Actions
Generative AI must not be used to perform actions that could physically harm a person, control equipment, or alter settings that impact human safety. These actions require deterministic, verifiable code and strict safety protocols.
✔Summary: AI can assist, but life-critical actions must always remain human-controlled.
Governing the Future of AI Responsibly
The 6 Laws of AI Agents provide a blueprint for deploying AI responsibly in the enterprise. By emphasizing transparency, ownership, disclosure, human oversight, and safety, organizations can embrace AI innovation without compromising trust.
At Augmentir, we believe AI should augment—not replace—human intelligence, and these laws ensure that principle is upheld.
https://www.augmentir.com/wp-content/uploads/2025/10/6-laws-of-ai-agents.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2025-10-01 13:35:102025-10-01 16:47:18The 6 Laws of AI Agents: Building Trust, Transparency, and Safety in AI
Learn how shop floor data capture improves manufacturing efficiency, quality, and agility. Discover how Augmentir’s AI-powered connected worker platform transforms real-time data collection on the shop floor.
Shop floor data capture is the process of collecting real-time information from manufacturing operations—including machine performance, labor activity, and production status—to improve visibility and decision-making. Connected worker platforms streamline and enhance this process by embedding data capture into digital workflows, enabling accurate, real-time input directly from frontline workers.
Read this article to learn more about shop floor data capture in manufacturing:
Shop Floor Data Capture (SFDC) is the process of collecting real-time operational data from the manufacturing floor. This includes tracking machine status, work order progress, labor inputs, quality checks, safety reports, material usage, and unplanned downtime—essentially, any data that reflects how work is being done in real-time.
Modern SFDC systems gather this information digitally using a combination of mobile devices, connected worker technology, sensors, connected machines (Industrial IoT), and software platforms, replacing traditional paper forms, spreadsheets, and delayed manual entry.
Why Shop Floor Data Capture Matters in Manufacturing Today
For manufacturers, every second on the shop floor counts. Without accurate, real-time insight into what’s happening, teams are forced to rely on outdated reports, gut feelings, or tribal knowledge to make decisions. This leads to:
Production delays
Low first-pass yield
Excessive downtime
Underutilized labor
Missed improvement opportunities
Shop floor data capture bridges the gap between what’s planned and what’s actually happening. When data is captured as work occurs, manufacturers gain the visibility needed to:
Identify inefficiencies immediately
Pinpoint training gaps or human error, which according to OSHA makes up 80-90 percent of serious injuries in the workplace.
Improve scheduling and resource allocation
Make data-driven decisions for continuous improvement
Who Benefits from Shop Floor Data Capture?
Shop floor data capture benefits multiple roles across manufacturing operations:
Operations Managers
Gain real-time visibility into production
Identify areas for process improvement
Supervisors & Line Leaders
Track shift performance and labor productivity
Ensure compliance with standard work
Continuous Improvement Teams
Analyze trends and root causes using accurate, structured data
Measure impact of Kaizen events or Lean initiatives
Quality Assurance
Detect deviations and non-conformances quickly
Link quality issues to specific operators, machines, or conditions
Executives
Align factory performance with strategic KPIs
Justify investments in digital transformation with hard data
Common Use Cases for Shop Floor Data Collection
1. Production Tracking
Capture cycle times, completion rates, and progress toward production targets.
2. Labor Time Reporting
Track how operators spend time on tasks, setups, changeovers, and idle periods.
3. Quality Checks
Real-time data collection with digital checklists and issue reporting—detect deviations and non-conformances quickly and link quality issues to specific operators, machines, or conditions.
Quality use case for shop floor data collection using the Augmentir Connected Worker Platform
Use modern software tools to support Statistical Process Control (SPC) data collection via mobile devices, allowing operators to input measurements directly from the shop floor. Visual dashboards and interactive SPC charts help teams quickly identify and respond to process variations.
6. Digital Work Instructions with Feedback
Capture data as operators follow digital work instructions—ensuring standard work is followed and insights are logged automatically.
7. Training and Skill Tracking
Use skills management tools to monitor how skill levels and training impact performance, and identify upskilling opportunities.
Shop Floor Data Capture is the First Step Toward Industry 4.0
Capturing accurate shop floor data is not just an operational improvement—it’s a foundational step in the journey toward smart manufacturing. By digitizing and automating data collection, manufacturers can:
Enable predictive maintenance
Support AI-driven decision-making
Improve workforce development strategies
Achieve greater agility in response to market changes
How Technology is Transforming Shop Floor Data Capture
Technology is revolutionizing how manufacturers collect and use data on the shop floor. Traditional manual methods—like paper checklists, spreadsheets, and standalone terminals—are being replaced by digital, connected solutions that enable real-time visibility, reduce errors, and unlock continuous improvement.
One of the most impactful advancements is the rise of Connected Worker Platforms. These platforms equip frontline workers with mobile devices, wearables, or voice-enabled tools that guide them through tasks while automatically capturing data in the flow of work. This eliminates the need for redundant data entry and ensures that information is accurate, consistent, and immediately available for analysis.
Adding to this transformation is the emergence of AI-powered digital assistants, such as Augie, Augmentir’s GenAI Assistant for Manufacturing. These AI tools analyze the data captured from the shop floor and deliver proactive insights, recommendations, and real-time support to workers and supervisors. Whether it’s identifying patterns in downtime, highlighting skill gaps, or surfacing quality issues, AI Agents enable a more intelligent, adaptive approach to managing operations.
Key Technology Advancements Driving Change:
GenAI Assistants like Augie: Transform raw data into intelligent, actionable insights that drive continuous improvement and smarter decision-making.
Connected Worker Platforms: Digitize frontline work and embed data capture into standard processes.
Mobile and Wearable Devices: Allow workers to input data quickly and hands-free, improving efficiency and safety.
IoT Sensors and Smart Machines: Enable automatic capture of machine data without human input.
Cloud and Edge Computing: Ensure real-time access to data across facilities and roles.
By integrating these technologies, manufacturers are not only improving data collection but also building a foundation for a more agile, efficient, and intelligent factory floor.
How Augmentir Elevates Shop Floor Data Capture
Augmentir goes beyond basic data collection by embedding data capture directly into the flow of work through AI-powered connected worker tools. Rather than asking operators to fill out separate forms or spreadsheets, data is automatically gathered as workers execute tasks using digital work instructions, smart checklists, or mobile guidance.The
Augmentir platform is a suite of connected worker software tools that helps customers digitize and optimize all frontline processes including autonomous and preventive maintenance, quality, safety, asset management, and workforce training and development. The solution combines skills management, digital workflow, collaboration, and knowledge sharing to deliver continuous value in a wide range of verticals.
At the core of this system is Augie, Augmentir’s Suite of GenAI tools. Augie continuously monitors captured data to deliver intelligent, context-aware insights to workers and supervisors—helping identify inefficiencies, recommend improvements, and provide real-time support when it’s needed most.
Key Capabilities:
Embedded Data Capture: Workers enter data naturally during task execution—no extra steps required.
Automated Time and Activity Tracking: AI accurately logs who did what, when, and how long it took.
AI-Driven Insights: Augie analyzes workforce and operational data to uncover skill gaps, detect process variation, and suggest workflow optimizations.
Closed-Loop Feedback: Capture feedback from the frontline to continuously improve instructions and processes.
Seamless Integrations: Sync with ERP, MES, or CMMS systems to create a unified data environment.
Real-Time Assistance with Augie: Augie acts as a digital assistant on the shop floor, guiding workers, surfacing knowledge, and enabling just-in-time learning and decision support.
With Augmentir, manufacturers move from reactive firefighting to proactive optimization—unlocking measurable gains in productivity, quality, and agility, all powered by real-time data and intelligent AI support.
Ready to Modernize Your Shop Floor?
With Augmentir, you can start capturing high-quality shop floor data in days—not months. Empower your teams with tools that make work easier while giving you the insight to continuously improve operations.
Request a demo or Contact us to see how Augmentir can help.
Learn how to standardize quality assurance procedures in manufacturing to improve overall quality and reduce errors.
It takes implementing just one wrong procedure for a product to end up defective and nowhere near ready for customer delivery. That’s why it’s important to standardize quality assurance (QA) procedures to ensure conformity on the shop floor and prevent product malfunctions.
But what is quality assurance? According to TechTarget, it is a process used to determine whether a product or service meets necessary requirements, in manufacturing specifically these are required standards for distribution. In a nutshell, QA procedures ensure customers receive quality products that are free of defects.
Learn how to standardize quality assurance procedures in manufacturing by exploring the following content:
QA procedures are a systematic process of establishing and maintaining set requirements for manufacturing reliable products and services. These procedures should be standardized by setting up a quality assurance system for workers to access. There, they can see how to complete certain tasks to avoid errors on the production floor.
Quality assurance methods can be categorized into three types, which we explain in the table below.
Type of QA method
Description
Example
Failure testing
This is the process of testing a product to see if it can withstand stress. The purpose is to identify any deficiencies.
Manufacturers may place a product under heat, pressure, or vibration to test outcomes.
Statistical process control (SPC)
SPC is an industry-standard practice for measuring and controlling product quality during the production process. Data is collected by measuring process inputs (dependent variables) in real time. This data is then visualized in SPC charts with predetermined control limits based on how a type of product is expected to perform.
A manufacturing line would apply statistical and analytical tools to monitor input variables and look for excesses or waste.
Total quality management (TQM)
TQM is the idea that every employee, from assembly line workers to leadership, is committed to improving processes, products, and services.
TQM may be implemented to raise overall productivity and make a manufacturer more competitive.
How to standardize quality assurance procedures
Quality assurance procedures help manufacturers develop products and services that meet customers’ needs and expectations. If implemented successfully, QA can catch any defects before they arise and substantially increase product quality.
It’s also vital to implement a quality assurance system to improve efficiency. Developing a unified system makes it easier to incrementally improve your production processes, and it’s essential for standardizing your quality assurance procedures.
Read on about the seven steps for successful QA implementation:
Step 1: Define Organizational Goals
Successful manufacturing QA begins by identifying how workers’ jobs are tied to an organization’s goals. It’s crucial for workers to know their company’s mission and how they fit into it. When employees understand how their individual goals relate to the organization’s goals, it can boost worker confidence — and in turn, production efficiency.
Step 2: Pinpoint Necessary Success Factors
It’s important to list the factors that make your quality assurance process successful. For instance, factors can include production processes, technical or customer support, and other things that make your organization great. Creating a list of major factors that contribute to company achievements will make it easier to update and manage those factors later on.
Step 3: Identify Your Customer Base
It’s vital to define your client case. If you know your customer, you’re more likely to create products and services that they would value.
Step 4: Gather Customer Feedback
Once you’ve established your customer base, it’s vital to incorporate what they think about your products and services. Frequent customer feedback can keep your quality assurance on track since it helps you identify and resolve product issues before they become critical problems. Reports can be gathered though surveys, email, phone, focus groups, or other methods. The goal is to achieve continuous feedback regardless of which methods you choose.
Step 5: Strive for Continuous Improvement
Quality assurance goes hand in hand with continuous improvement. The information you’ve gathered from customer surveys or other methods can now be used to implement any needed changes to your quality assurance process.
Continuous improvement can also be in the form of customer service training, changes to production processes, improvements to products or services, or anything that adds value to your organization.
Whatever you do, it’s crucial to study customer comments and use them to enhance operational procedures to ensure you’re delivering products that bring value and sell.
Step 6: Find QA Management Software
Once you’ve established the above steps, it’s time to start thinking about which quality QA software, or system, will help you better implement QA procedures. Picking the right software will aid with maintaining and improving production processes.
Step 7: Assess Results
Lastly, it’s important to measure your results. Your main goal is to ensure that your business meets the needs of each customer. Create measurable objectives for employees so that everyone knows what needs to be accomplished in a timely manner. If goals aren’t met, make sure workers are clear about what actions need to be taken to meet client satisfaction.
Take note: If your manufacturing firm does not reach its goals, it is hard to show a positive ROI to stakeholders. That’s why taking corrective action to meet company targets is more imperative than ever before.
Benefits of Implementing QA Procedures in Manufacturing
Quality assurance in manufacturing can offer a wide variety of benefits if management makes it a priority.
Some benefits of standardizing QA procedures include:
Cost-effectiveness: When done right, QA can prevent quality product issues before hitting the market. For instance, manufacturers won’t have to worry about scrapped parts, product returns, or other expenses due to poor-quality goods.
Greater workplace efficiency: Manufacturers will be able to better allot resources like time, money, and warehouse space if fewer product deficiencies exist. It boils down to this: it takes fewer resources to develop quality items if processes are in place to support the feat of QA procedures.
Enhanced Customer satisfaction: Customers will almost surely receive quality products in a timely manner if workers employ quality assurance techniques. If fewer product malfunctions exist, customers are more likely to keep coming back for more. In the end, it’s a win-win situation for both businesses and clients alike.
Industrial companies use Augmentir’s breakthrough system to standardize and optimize quality assurance procedures in manufacturing. With Augmentir, you will experience fewer errors and reduced product defect rates with our connected worker solution. Learn more about our quality use cases.
Contact us for a live demo to start optimizing your frontline operations today!
https://www.augmentir.com/wp-content/uploads/2022/10/quality-assurance-procedures-manufacturing.png6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2022-10-20 02:31:522025-08-10 11:04:57How to Standardize Quality Assurance Procedures in Manufacturing
Augmentir recognized by the Brandon Hall Group for the “Best Advance in Generative AI for Business Impact”, wins gold in the 2024 Technology Excellence Awards.
We did it again!
We are excited to announce today that Augmentir won Gold in the 2024 Brandon Hall Group Excellence in Technology Awards for “Best Advance in Generative AI for Business Impact“.
The 2024 Brandon Hall Group Excellence in Awards™ are given for work in Learning and Development, Talent Management, Talent Acquisition, Human Resources, Sales Enablement, Future of Work, and Education Technology. Augmentir received its gold award in the Future of Work category based on our breakthrough, innovative use of Generative AI to address skilled labor shortages and workforce challenges that are crippling the manufacturing industry today.
Entries were evaluated by a panel of veteran, independent senior industry experts, Brandon Hall Group analysts, and executives based upon these criteria: fit the need, program design, functionality, innovation, and overall measurable benefits.
“In our 31st year, the Excellence in Technology Awards continue to showcase the best innovations in learning, talent management, talent acquisition, HR, workforce management, and sales enablement technologies. We are proud to receive applications from a diverse range of organizations globally, reflecting the ever-evolving landscape of technology solutions,” said Brandon Hall Group Chief Operating Officer Rachel Cooke, leader of the Excellence Awards program.
Augmentir’s generative AI solution – Augie™ – is a central component to the Augmentir Connected Worker platform. Augie is a generative AI assistant that improves operational efficiency and supports today’s less experienced frontline workforce through faster problem-solving, proactive insights, data analysis, rapid content creation, and enhanced decision-making.
Augmentir recently unveiled powerful new updates to Augie, and launched the industry’s first Industrial Generative AI Suite, targeted towards improving safety, quality, and productivity for the industrial frontline workforce. Augie’s suite of gen AI services expand on the platform’s existing capabilities, which have been in use by leading manufacturers for over a year, transforming operations and addressing the skilled labor shortage through advanced troubleshooting and real-time digital assistance to frontline workers. The Augie Industrial Gen AI Suite includes:
Augie Industrial Work Assistant Provide real-time support and guidance to workers on the floor or in the field. Augie helps workers with standard work, troubleshooting, and information access.
Augie Content Assistant Automatically convert existing digital content (Word Excel, PDF, etc) into native Augmentir Work instructions, SOPs, OPLs, CILs, Checklists, etc., accelerating deployment. Generate training, checklists, and quizzes from a wide range of source types including images, manuals, free-form tests, etc., to streamline worker training and onboarding.
Augie Data Assistant Augie provides insights from any source of operational data, including standard datasets such as Skills, Standard Work, Safety, and Work Execution, as well as customer-specific datasets generated through Augmentir’s report configurator. Augie eliminates the need for “report writing” and through its conversational interface answers questions, performs math, and generates graphical reports, increasing responsiveness.
Augie Extensibility Assistant Augie increases the productivity of developers building new functions and supporting existing user-defined functions within Augmentir’s extensibility framework. Augmentir’s unique Platform-as-a-Service offering empowers customers and partners to create unique solutions that solve critical business challenges—a capability that no other platform on the market offers.
Augie Industrial GenAI-as-a-Service As an industry first, Augie exposes its GenAI capabilities as APIs within Augmentir’s extensibility framework. This allows companies and partners to create innovative, customized GenAI solutions tailored to business, or industry-specific needs and use cases. Commonly used APIs include: translateText enabling on-the-fly translation of dynamic content, and imageQA, enabling direct comparison or summarization of images, supporting critical applications in Quality, Safety, and Operations.
“We’re thrilled to be recognized by the Brandon Hall Group for bringing the transformative power of generative AI to industrial frontline operational processes,” said Russ Fadel, CEO of Augmentir. “Just as we have seen GenAI deliver transformational value to the consumer and enterprise, the Augie Suite provides the tools to enable companies to empower their frontline workers, regardless of experience, to perform with higher levels of safety and productivity. Additionally, this provides the tools for our partners to build innovative use cases to solve previously unsolvable problems.”
Augmentir introduced Augie in early 2023, becoming the first software provider in the manufacturing sector to offer a generative AI solution focused on the industrial frontline workforce. Since its launch, Augie has been adopted by industry leaders across all manufacturing and production verticals, helping prevent safety and quality issues at the point of work, driving operational efficiency, and giving frontline workers the tools, guidance, and support they need to do their best work.
Augie’s generative AI capabilities are built into the core of the Augmentir platform, so customers can quickly and securely leverage the latest AI advances within the framework of digital collaboration, skills management, and work execution. This allows customers to leverage existing data, documents, applications, and their existing tribal knowledge, increasing their ROI.
Interested in learning more?
If you’d like to learn more about Augmentir and see how our AI-powered connected worker platform enables Augmented Connected Worker initiatives to improve safety, quality, and productivity across your workforce, schedule a demo with one of our product experts.
https://www.augmentir.com/wp-content/uploads/2024/12/brandon-hall-group-gold-award-augmentir-future-of-work-generative-ai.webp12602400Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2024-12-10 15:02:322025-08-07 15:29:18Augmentir Wins Gold at 2024 Brandon Hall Group Excellence in Technology Awards
Augmentir was recently recognized by Verdantix as one of the top 10 best AI-powered industrial copilot vendors offering comprehensive solutions for workforce management and productivity efficiency.
Generative AI Industrial Copilots—AI assistants powered by large language models (LLMs) and tailored for manufacturing environments—are rapidly becoming essential tools for modern manufacturers. These copilots provide frontline workers and engineers with real-time, context-aware guidance, troubleshooting support, and automated documentation, all through natural language interactions.
Their rise is driven by critical industry challenges: a widening skills gap as experienced workers retire, ongoing workforce shortages, and the urgent need to boost productivity and operational efficiency. By capturing institutional knowledge and delivering it instantly to less-experienced workers, industrial copilots help manufacturers maintain performance, reduce downtime, improve safety, and accelerate digital transformation efforts.
Verdantix, an independent research and advisory firm that provides data-driven insights and strategic guidance on digital strategies for industrial organizations, recently covered the topic of generative AI industrial copilots in a market insights report. Verdantix’s market insight report highlights 10 innovative industrial copilot vendors delivering robust solutions for workforce management and productivity optimization. Industrial leaders can leverage this report to deepen their understanding of AI-driven technologies and explore how these solutions can support their own industrial transformation efforts.
Augmentir was recognized by Verdantix as one of the Top 10 Gen-AI-powered Industrial Copilot Vendors to Watch for 2025.
Top 10 Industrial Copilot Vendors
Here are the top 10 GenAI-Powered Industrial Copilot Vendors To Watch In 2025 as reported by Verdantix:
Augmentir – Augmentir’s generative AI assistant, Augie™, is a transformative tool designed to enhance industrial operations by providing real-time, context-aware support to frontline workers. Augie integrates data from various sources—including operational systems, training modules, and workforce management platforms—to deliver personalized guidance, streamline workflows, and facilitate rapid content creation.
ABB – ABB’s Genix Copilot, developed in collaboration with Microsoft, integrates large language models like GPT-4 to enhance industrial operations. It provides real-time, contextual insights to improve efficiency, productivity, and sustainability across sectors such as energy and utilities.
AVEVA – AVEVA, now part of Schneider Electric, has developed an Industrial AI Assistant, built on Microsoft Azure, that offers a conversational interface for users to access and summarize operational data. This assistant aims to improve decision-making and efficiency in industrial processes.
C3 AI – C3 AI‘s Generative AI Suite provides domain-specific solutions to assist technicians with equipment troubleshooting and reduce training time. The suite enables enterprise users to rapidly access and act on data through intuitive search and chat interfaces.
Cognite – Cognite‘s Generative AI Copilot, integrated within its Data Fusion platform, delivers real-time, contextualized insights for industrial operations. It enhances decision-making by providing a centralized view of industrial data, aiding in safety, reliability, and quality management.
IBM– IBM’s Copilot Runway assists enterprises in creating, customizing, and managing AI copilots, including integration with Microsoft 365. This offering aims to enhance productivity and drive business transformation through seamless AI adoption.
Nanoprecise – Nanoprecise’s ReKurv.ai is a generative AI solution designed for maintenance professionals in industrial environments. It offers real-time, contextual answers based on equipment behavior and operational data to enhance decision-making on factory floors.
Palantir – Palantir’s Artificial Intelligence Platform (AIP) connects AI with data and operations to drive automation across processes. It provides tools for building AI-driven functions and managing agents, facilitating real-time decision-making in critical contexts.
Siemens – Siemens’ Industrial Copilot, developed with Microsoft, is a generative AI assistant designed to enhance human-machine collaboration. It assists staff in designing products and organizing production and maintenance processes, aiming to improve productivity across industries.
SymphonyAI – SymphonyAI offers AI-driven solutions tailored for various industries, focusing on enhancing operational efficiency and decision-making. Their platforms integrate generative AI to provide actionable insights and improve business outcomes.
These companies, along with Augmentir, represent a transformative shift in how industrial leaders are deploying GenAI—not just to automate tasks, but to empower frontline workforces and drive measurable operational gains.
Key Benefits of Industrial Copilots
Industrial copilots offer a range of transformative benefits across operations, maintenance, training, and safety. Here are some of the key benefits:
Operational Efficiency & Productivity
Task Automation: Copilots can automate repetitive administrative tasks such as work order generation, data entry, and scheduling, freeing up time for skilled workers.
Real-Time Assistance: Provide workers with instant access to SOPs, manuals, and troubleshooting guides, improving first-time fix rates and reducing downtime.
Intelligent Recommendations: Suggest optimal next steps, tools, or parts based on contextual data, enhancing decision-making on the shop floor.
Data-Driven Insights
Contextualized Information: Copilots integrate data from multiple sources (ERP, CMMS, sensors, IoT) and present it in a unified, actionable format.
Anomaly Detection: Use AI to detect trends or anomalies in equipment performance or worker activity that could indicate operational risks or inefficiencies.
Knowledge Retention & Training
Just-in-Time Learning: Provide on-demand guidance and microlearning in the flow of work, tailored to workers’ roles and skill levels.
Knowledge Capture: Automatically document expert procedures and best practices to ensure tribal knowledge is retained and reused.
Safety & Compliance
Proactive Hazard Alerts: Warn workers of unsafe conditions based on environmental data, worker behavior, or equipment status.
Audit Support: Maintain up-to-date logs and documentation for compliance with industry regulations and standards.
Scalability & Workforce Empowerment
Support for Multi-Lingual & Diverse Teams: Enable consistent communication and guidance across geographically dispersed and multilingual teams.
Worker Empowerment: Give frontline workers more autonomy through AI guidance, increasing engagement and reducing reliance on supervisory intervention.
Augie™: An Industrial Copilot to Empower the Frontline Workforce
Introduced in early 2023, Augie™ is an industrial copilot designed specifically for the industrial frontline. Unlike traditional tools that rely heavily on equipment data alone, Augie™ integrates insights from frontline operations, training, engineering, and workforce data to deliver real-time, contextual support to frontline workers and supervisors.
Key Features Behind Verdantix Recognition
Verdantix highlighted Augmentir due to several standout capabilities within the Augie™ industrial copilot:
Industrial Work Assistant
Provide real-time support and guidance to workers on the floor or in the field. Augie helps workers with standard work, troubleshooting, and information access.
Content Assistant
Automatically converts standard files (Word, Excel, PDFs) into smart digital workflows such as SOPs and checklists. Augie can take your existing content and generate digital, smart forms, checklists, and interactive work procedures. Augie accelerates your transition to a paperless operation, and provides a robust tool for capturing tribal knowledge and converting it into digital corporate assets.
Operations Data Assistant
Interpret operational data through natural language queries, eliminating the need for complex reports or dashboards. The Augie industrial copilot helps operations leaders gain insights into your frontline operations by understanding and summarizing your operational data, generating reports, and providing insights into continuous improvement opportunities.
Extensibility Assistant
Offers developers tools to build custom GenAI experiences through user-defined functions and APIs. The Augie Extensibility Assistant from Augmentir empowers industrial companies to go beyond basic generative AI by enabling more intelligent and autonomous support for frontline operations. Through its seamless integration with Augmentir’s AI Agent Builder, Augie allows users to create and deploy AI agents that can interact with and analyze operational data, trigger automated workflows, and respond contextually to frontline needs. This extensibility framework lets manufacturers tailor AI assistance to their unique environments—connecting to third-party systems, retrieving and acting on data, and continuously learning from worker behavior and outcomes. The result is a scalable, adaptive solution that extends GenAI from simple question-answering to proactive, intelligent task support across the digital thread.
Solving Real Industrial Challenges
The industrial sector faces a range of challenges: growing skills gaps, legacy processes, inconsistent quality, and labor shortages. Augie™ directly addresses these by:
Boosting workforce performance with personalized, AI-driven task support.
Improving decision-making via fast access to operational and procedural knowledge.
Accelerating continuous improvement by uncovering inefficiencies through embedded data analytics.
The Future of Frontline Work, Powered by the Augie Industrial Copilot
Augmentir’s inclusion in Verdantix’s Top 10 GenAI Industrial Copilot Vendors watch list underscores its leadership in shaping the next generation of intelligent, AI-powered industrial tools. As frontline work evolves, platforms like Augie will be instrumental in bridging workforce gaps, maximizing productivity, and enabling safer, smarter operations.
Request a demo and see how Augie is redefining frontline performance.
Recently, Augmentir completed a rigorous qualification audit as part of a Tier 1 Pharmaceutical Manufacturing company’s Good Manufacturing Practice (GMP), and we are pleased to announce that our product successfully passed the audit.
A recent article published by The Washington Post shows some shocking numbers on the amount of Americans leaving their jobs over the past year. It’s no surprise that hotel and restaurant workers are resigning in high numbers due to the pandemic, but what is surprising is the fact that the manufacturing industry has been hit the hardest with “a nearly 60 percent jump” compared to pre-pandemic numbers. This “Great Resignation in Manufacturing” is the most of any industry, including hospitality, retail, and restaurants, which have seen about a 30% jump in resignations.
However, if you dig deeper, this trend isn’t new. This recent increase in job quitting in manufacturing has simply magnified a problem that had already been brewing for years, even prior to the start of the pandemic. In fact, in the four years prior to the pandemic (2015-2019), the average tenure rate in manufacture had decreased by 20% (US Bureau of Labor Statistics).
This accelerating workforce crisis is placing increased pressure on manufacturers and creating significant operational problems. The sector that was already stressed with a tight labor market, rapidly retiring baby-boomer generation, and the growing skills gap is now facing an increasingly unpredictable and diverse workforce. The variability in the workforce is making it difficult, if not impossible to meet safety and quality standards, or productivity goals.
Manufacturing leaders’ new normal consists of shorter tenures, an unpredictable workforce, and the struggle to fill an unprecedented number of jobs. These leaders in the manufacturing sector are facing this reality and looking for ways to adjust to their new normal of building a flexible, safe and appealing workforce. As a result, managers are being forced to rethink traditional onboarding and training processes. In fact, the entire “Hire to Retire” process needs to be re-imagined. It’s not the same workforce that our grandfather’s experienced, and it’s time for a change.
The Augmented, Flexible Workforce of the Future
The reality is that this problem is not going away. The Great Resignation in manufacturing has created a permanent shift, and manufacturers must begin to think about adapting their hiring, onboarding, and training processes to support the future workforce in manufacturing – an Augmented, Flexible Workforce.
What does this mean?
It means adopting new software tools to support a more efficient “hire to retire” process to enable companies to operate in a more flexible and resilient manner.
It means starting to understand your workforce at an individual level and using data to intelligently closes skills gaps at the moment of need and enables autonomous work.
And it means taking advantage of data. More specifically, real-time workforce intelligence that can provide insights into training, guidance, and support needs.
Investing in AI-powered connected worker technology is one way to boost this operational resiliency. Many manufacturing companies are using digital Connected Worker technology and AI to transform how they hire, onboard, train, and deliver on-the-job guidance and support. AI-based connected worker software provides a data-driven approach that helps train, guide, and support today’s dynamic workforces by combining digital work instructions, remote collaboration, and advanced on-the-job training capabilities.
As workers become more connected, manufacturers have access to a new rich source of activity, execution, and tribal data, and with proper AI tools can gain insights into areas where the largest improvement opportunities exist. Artificial Intelligence lays a data-driven foundation for continuous improvement in the areas of performance support, training, and workforce development, setting the stage to address the needs of today’s constantly changing workforce. Today’s workers embrace change and expect technology, support and modern tools to help them do their jobs.
https://www.augmentir.com/wp-content/uploads/2022/02/great-resignation-in-manufacturing.jpg6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2022-02-17 02:31:322025-07-04 11:22:47The Great Resignation in Manufacturing
After more than a year of virtual conferences, we were finally able to participate in person at the AI Manufacturing conference in Dallas early this November and discuss how AI is shaping the future of the manufacturing workforce.
After more than a year of virtual conferences, we were finally able to participate in person at the AI Manufacturing conference in Dallas early this November. This year’s event was hybrid, face-to-face on November 3 and 4th, and virtually on November 5th. While it was refreshing to be able to network face to face with leaders in the Manufacturing industry, it was great to have the opportunity to also network virtually on November 5th. If you aren’t familiar with the AI Manufacturing conference, this conference is the leading Artificial Intelligence event for Manufacturing Industries. This year’s event focused on:
The use of AI to Improve Quality, Reduce Defects, and Increase Profits
Developing a Digital Twin to Optimize Plant Operations
Using Building Blocks to Modernize Manufacturing Activities and Facilitate Growth
Designing Products Enabled by Additive and Hybrid Manufacturing Techniques
Exploring the Use of AI in Industrial Attacks and Defense
Using AI to Unlock the True Potential of Today’s Modern, Connected Workforce
Dave Landreth, Augmentir’s Head of Customer Strategy had the opportunity to present on “Using AI to Unlock to the True Potential of Today’s Connected Workforce”. In this session, he discussed the variability of the workforce with generations, how they need to be trained differently, and how AI can assist in worker proficiency. Dave also discussed Bob Mosher’s 5 moments of need and how AI can be applied at the time of learning.
The Misunderstood Fear of AI
Our founders saw that the humanistic approach was missing with traditional connected worker platforms and realized that AI was the key to saving the manufacturing world and unlocking worker potential. However, companies are reluctant to adopt AI in fear that automation will take over and eventually replace human workers in manufacturing. Others fear that AI would be used negatively to track workers, in a “big brother” type of way.
As we’ve seen with our customers, this couldn’t be farther from the truth. When AI is leveraged ethically with the workforce in mind, it can be used to help improve and ultimately grow the talent of your workers. Assessing workers on their performance has been done for years through subjective performance reviews. Using AI allows the assessments to be based on data and can provide a path forward for worker improvement and continued growth.
Understanding Today’s Struggles Within Manufacturing
The struggles that manufacturers face today aren’t the same struggles that were present 40 years ago. One of the number one issues in manufacturing is hiring. Today, most manufacturers believe that hiring is a risk, with a limited pool of candidates. They are struggling with employees who don’t have the needed skill set and are questioning how they can train them and evaluate their performance.
Manufacturing companies also struggle with retaining employees. We are all aware of the workforce retention issues right now. Employees are feeling like they aren’t heard and that they can’t contribute to the company, which causes them to look for a new career. There is also the struggle of thoughtful upskilling, meaning that formal training programs only recognize one type of worker. The average manufacturing plant sees 4 generations of workers, ranging from those fresh out of high school to the ones that have worked on a plant floor for 40+ years. Different generations learn differently and require different levels of support. There isn’t a one size fits all approach for teaching different generations.
Another challenge with the workforce that isn’t as obvious, is with mergers and acquisitions. An acquisition means that companies now consist of two workforces doing things differently and needing to understand what part of procedures from the newly acquired company is worth incorporating into the existing procedures.
Leveraging AI to Help Build and Grow a Top Performing Workforce
AI is uniquely suited to solve these challenges, and we recognized that early on at Augmentir. We started looking at how AI could help build and grow a top performing workforce. One way AI can help is the ability to hire for potential by increasing the hiring of candidates to those not as skilled. AI allows companies to understand a worker’s skillset and provides the ability for personalized workflows to guide them in the context of work while they are doing their job, whether it’s a new worker or one with dozens of years of experience. AI can also help with the “Right person – Right Job – Right Time” approach – always ensuring that the correct person is performing the task at the most efficient time.
The use of AI allows all workers to contribute by allowing inline feedback to optimize work procedures. In addition, AI can be used to ensure personalized career job competency allows workers to be hired even if they do not have the optimal set of skills and experience. Measuring a worker’s proficiency when they are completing the work allows the worker to focus on each specific step and guides them at the time of need, instead of during classroom training. AI provides workers with predictive and stable data to help them grow in their roles. Having a data-driven way to measure success and provide advancement opportunities helps establish career paths as well as opportunities to grow.
With an AI-based onboarding approach, organizations are able to hire a wider range of individuals with varying skill sets. If we can teach someone in the context of doing their work, onboarding time is reduced due to being able to train them in the field. We also see an increase in productivity and are constantly evolving their learnings. When workers feel included and confident about their careers, they are also more likely to want to stay and grow with the company. The ability to train workers in the field while doing their jobs with AI personalization allows you to clearly and quickly assess how a worker is doing, where you focus the help to them, and driving those 1:1 work procedures is a game-changer.
AI in Manufacturing will solve many of the challenges that we are seeing.
Learning & Development and the 5 Moments of Need
The Five Moments of Need methodology was created by Bob Mosher, a thought leader in learning and development with over 30 years of experience. He realized that after 20 years, classroom teaching was the wrong approach since it rarely teaches you things that you do in your job on the shop floor. Classroom learning allows an individual to gain a certain level of confidence, but quickly falls off when it’s time to apply it within context to a given workflow.
According to Bob’s methodology, the 5 moments when our workforce needs knowledge and information consists of:
When people are learning how to do something for the first time (New).
When people are expanding the breadth and depth of what they have learned (More).
When they need to act upon what they have learned, which includes planning what they will do, remembering what they may have forgotten, or adapting their performance to a unique situation (Apply).
When problems arise, or things break or don’t work the way they were intended (Solve).
When people need to learn a new way of doing something, which requires them to change skills that are deeply ingrained in their performance practices (Change).
The approach that Bob and his team adopted in the last 10 years is to think more about performance support. The variability of the workforce, both skilled and young, proves that there’s not a one size fits all approach. This is where AI comes in: being able to deliver personalized work procedures for every worker, allowing for continuous learning and growth. Based on proficiency, there may be a more guided set of work instructions, a session with a remote expert, or a supervisor sign-off required in order to complete the job on quality and on schedule. AI can also be used to continuously measure and assess how the workers are doing. This is where organizations can start seeing growth within their workforce.
Looking Ahead
We had a blast at this year’s AI Manufacturing conference and are already looking forward to another successful event next year! If you’re interested in learning more about why AI is an essential tool in digital transformation, from reducing costs and downtime to improving over quality and productivity, we’d highly suggest considering attending next year. In the meantime, if you’re looking for information surrounding AI, digital transformation, and building a connected workforce, check out our eBook: “Building a Modern, Connected Workforce with AI”.
Discover how Connected Worker platforms like Augmentir are transforming safety compliance in manufacturing and industrial sectors. From digitized SOPs to AI-powered insights, learn 5 powerful ways to improve EH&S.
In industries like manufacturing, energy, pharmaceuticals, and construction, Environmental, Health & Safety (EH&S) is not just a regulatory requirement—it’s central to operational integrity, workforce well-being, and brand trust. Yet many organizations still rely on outdated paper processes, static training programs, and fragmented safety communication systems.
As digital transformation accelerates across frontline operations, a new class of solutions is emerging: Connected Worker platforms. These tools empower industrial workers with mobile access to the information, training, and communication they need—exactly when and where they need it. When integrated into EH&S programs, they don’t just make safety easier to manage—they make it smarter, more scalable, and more resilient.
Backed by AI and real-time data, platforms like Augmentir are helping companies move from reactive safety management to proactive risk prevention.
Here are the top 5 ways Connected Worker tools are improving safety compliance in 2025 and beyond:
1. Digitizing and Standardizing Safety Procedures
Outdated SOPs, missing forms, manual permit to work processes, and inconsistent training delivery can all lead to non-compliance and unsafe conditions. Connected Worker tools eliminate these gaps by fully digitizing safety workflows—creating a single source of truth for the entire workforce.
Whether it’s a job safety analysis, equipment inspection, permit to work, or Lockout Tagout (LOTO) checklist, mobile connected worker applications ensure every worker has access to real-time, validated instructions. No printing. No ambiguity. Just operational consistency.
2. Real-Time Communication of Hazards and Safety Updates
Many industrial incidents are the result of slow or ineffective communication. Connected Worker platforms enhance situational awareness by enabling real-time messaging, collaboration, alerts, and escalation workflows.
If an unexpected hazard arises—say, a chemical leak or equipment fault—managers can instantly notify affected personnel, reroute workflows, or push emergency protocols. Workers, in turn, can report near misses, unsafe conditions, or noncompliance through voice commands, forms, or photos directly from the floor.
Result: A faster, closed-loop system for identifying and addressing safety risks before they escalate.
3. Delivering Embedded, Adaptive Safety Training
Traditional EH&S training is periodic, generic, and disconnected from actual work. In contrast, Connected Worker tools bring adaptive, on-demand microlearning directly into the flow of work.
Using Augmentir’s AI-powered connected worker platform, safety refreshers, toolbox talks, and task-specific training modules are delivered at the point of need—tailored to the worker’s skill level, recent behavior, or even risk profile.
Why it matters: Personalized safety education builds long-term retention and reduces costly retraining cycles.
4. Automating Safety Documentation and Compliance Readiness
Compliance is only as strong as its documentation. But manual reporting systems often result in incomplete records, delayed submissions, or errors that surface during audits.
Connected Worker platforms solve this by automatically capturing who did what, when, and how—across inspections, sign-offs, observations, and more. Every action is time-stamped, traceable, and ready for regulatory review, whether you’re governed by OSHA, ISO 45001, or industry-specific protocols.
Compliance advantage: Be audit-ready in minutes, not months.
5. Unlocking Predictive Safety Insights Through AI
EH&S leaders need to do more than react—they need to predict. With Connected Worker platforms, operational data becomes a strategic asset. Augmentir uses AI and machine learning to analyze safety behaviors, flag leading indicators of risk, and recommend interventions—before incidents occur.
This includes identifying trends such as repeated safety violations on a particular shift, increasing near-misses on certain equipment, or declining task proficiency in a subgroup of workers.
Forward-looking benefit: Transition from lagging indicators (like incident rates) to leading indicators that drive a culture of safety excellence.
How Augmentir is Revolutionizing Safety Compliance
Augmentir’s platform is at the forefront of transforming how industrial companies manage EH&S. By embedding safety into daily operations, it helps organizations go beyond compliance to create a culture of safety ownership.
Key innovations Augmentir brings to safety compliance:
AI-driven Safety Intelligence: Augmentir’s AI identifies risk trends across tasks, teams, and sites, helping safety leaders implement targeted improvements.
Smart Workflows: Every safety-critical task is embedded into digital workflows that adapt to individual performance and conditions in real time.
Continuous Worker Feedback: Built-in feedback loops ensure workers can raise issues, suggest improvements, and stay engaged with safety practices.
Performance-Linked Safety Coaching: Augmentir correlates safety metrics with individual skill profiles, prompting personalized coaching to address gaps before they become incidents.
Augmentir doesn’t just digitize safety—it makes it dynamic, intelligent, and fully integrated with operational execution. As a result, companies can achieve higher compliance rates, fewer incidents, and a more empowered frontline workforce.
Final Thoughts: EH&S in the Connected Era
LNS Research, a thought leader in the industrial space, recently identified EH&S as one of the most strategic areas impacted by Connected Worker technologies. As expectations rise—for safety, sustainability, and operational agility—the need to modernize your EH&S approach becomes non-negotiable.
Augmentir’s Connected Worker platform enables industrial companies to embed safety into every task, every worker, and every workflow. It’s time to stop managing safety in silos and start integrating it into the core of your operations.
Let’s talk: Request a demo to see how Augmentir can elevate your EH&S strategy.
