Cleveland, Ohio · Industrial Technology
Know what your factory is actually doing.
Anderion is building spatial and operational intelligence that connects machine activity, workforce availability, material movement, and production across the physical factory. Our goal is to uncover downtime and lost capacity, improve labor efficiency, and help manufacturers make better decisions using the equipment they already have.
Early-stage development · Seeking manufacturing pilot partners
The problem
Your factory has data. It doesn't have the full picture.
Machines report status and interruptions. ERP and MES systems provide production information. Timekeeping records labor hours. Material systems record inventory and deliveries. But these sources often don't explain how events affected one another.
People
Assignments, skills and labor hours
Machines
Status, interruptions and production activity
Material
Inventory, deliveries and work in process
Movement
People and material moving across the floor
Production
Orders, schedules and output from ERP and MES
Shared operational timeline
Schematic
The most expensive problems often occur between disconnected systems, not inside any one of them.
Anderion is being designed to connect those operational relationships.
The intelligence layer
Connect the events. Understand the loss.
Anderion is being designed to connect operational evidence into a shared timeline, so management can investigate likely contributing factors instead of reviewing separate metrics one system at a time.
Example · Press 4 work area
Illustrative scenario, not measured pilot data.
During one Press 4 stoppage
1Machine
Production at Press 4 stops.
- 2
People
The operator remains assigned to the work area.
- 3
Material
The material delivery arrives later than expected.
- 4
Shared context
The timeline shows a possible relationship between the late delivery and the stoppage.
- 5
Worth investigating
The missed production target becomes a cause worth investigating, with the evidence attached.
Across many events, shared context can reveal patterns and possible relationships. The aim is to show management where the evidence points and which causes are worth investigating, not to declare a cause automatically.
The platform
See the factory as one connected operation.
Anderion has built functioning Ops Intelligence software, the foundation for three connected capabilities. The views below show where the interface is heading, with simulated operational data, alongside a screenshot of the working prototype.
Workforce Flow
Understand how work moves.
Explore where people and materials move, where work waits, and how activity develops across workstations. Anderion is building spatial visibility to help manufacturers investigate congestion, repetitive travel, handoff delays, and opportunities to improve flow.
Operations
See the operation as a connected system.
Bring machine activity, production information, material availability, workforce context, and operational events together. Instead of analyzing disconnected reports, manufacturers can investigate how interruptions and constraints affect the wider operation.
Andy
Turn operational evidence into better decisions.
Andy is Anderion's reasoning layer, designed to connect operational events with their surrounding context, surface potential causes, and recommend actions worth evaluating. The goal is to help managers understand not only what happened, but what they might do next and how to measure the result.
Workforce-aware operations
The workforce and the machinery, connected.
Most plants can report equipment downtime, production status and labor records, but each in its own system.
By connecting machine status with workforce availability and role-specific qualifications, Anderion aims to reveal when equipment is waiting, qualified employees are available elsewhere, or a reassignment could help reduce downtime and unnecessary overtime.
Qualification information would come from a manufacturer's available employer records or integrations, and a recommendation depends on machine, workforce and spatial information being available and reliable enough to support it. This connected workflow is being developed and validated; Andy's recommendations remain subject to management review and approval.
Workforce Flow: Explore how people and activity move through a manufacturing facility. Visualize movement patterns, workstation activity, waiting time, and areas where congestion or unnecessary travel may occur.
Operations + Andy: Connect production issues, machine activity, work orders, and operational context. Andy is being developed to identify likely constraints, explain the supporting evidence, and recommend actions for managers to evaluate.
Prototype screenshot · Demonstration data: the Operations dashboard in the working software
How Andy is intended to work
Illustrative future-capability scenario, not a verified autonomous workflow. Andy recommends; managers decide.
1Observe
A CNC machine unexpectedly stops. Anderion's operational model is intended to connect the available machine, material and production information with spatial activity around that workstation.
2Understand
Andy could identify a possible material shortage as a likely cause and show the evidence behind it.
3Recommend
Andy could check for available inventory elsewhere in the facility and recommend a transfer for management approval.
4Verify
The system could then compare subsequent operating activity to see whether the intervention improved the situation.
Overview: See where movement, waiting, and congestion may be affecting operations. A spatial factory model brings together workforce activity, equipment, material movement, and potential bottlenecks in one connected view.
What we aim to reveal
Find what's slowing production down.
Downtime
Investigate the circumstances surrounding production interruptions.
Labor + Material Flow
Understand avoidable waiting, repetitive travel, congestion and handoffs, and recognize when qualified labor could be better allocated.
Production Capacity
Identify lost capacity where staffing, equipment, materials and process constraints overlap.
Automation Readiness
Understand repetitive or constrained workflows that may justify robotics or other forms of automation.
Automation readiness
Understand the workflow before automating it.
Manufacturers are weighing robotics, autonomous mobile robots and other automated systems. Deciding what to automate starts with a detailed understanding of how the work happens today.
Anderion's operational model is being built to provide that evidence: decision support for automation investments, not a system that controls equipment.
Questions Anderion is being built to help investigate
- What work should be automated?
- Where should robotics or autonomous equipment operate?
- Which material movements or repetitive tasks are suitable?
- What physical constraints exist?
- How should workflows change around automation?
- What economic benefit might justify the investment?
- After implementation, did the expected results actually occur?
Technology
Built for the factories that already exist.
Manufacturing plants run on equipment built across different decades. Many small and midsize manufacturers, including plants running legacy machinery, cannot justify replacing equipment or funding a large infrastructure project to understand how their operation performs.
Industrial intelligence without the costly overhaul.
Anderion is building a more affordable, accessible approach to industrial intelligence. By integrating with existing equipment, using targeted sensors where needed, and processing data locally, we're designing technology that helps manufacturers understand and improve their operations without requiring expensive, factory-wide infrastructure replacements.
Anderion's direction does not require a manufacturer to:
- Replace existing equipment
- Build a new factory
- Buy into one vendor's full technology ecosystem
- Take on a complete rip-and-replace project
Affordable industrial intelligence
Operational intelligence within reach of manufacturers that cannot justify large-scale modernization projects.
Compatibility with existing factories
Designed to work with existing equipment, operational systems and available data, rather than replacing machinery.
Targeted sensing
Additional sensors only where operational visibility is missing, not unnecessary systems across the entire facility.
Local-first architecture
On-premises processing, manufacturer control over operational data and less dependence on continuous cloud connectivity.
Practical implementation
Designed for simpler integration, repeatable deployment and less complexity for smaller manufacturing operations.
Existing Systems + Targeted Sensing
Plant systems and equipment signals where available; targeted sensing only where information is missing.
Factory Edge
Collection and normalization close to the production floor.
Operational + Spatial Events
Time-stamped, source-attributed records of what happened, and where.
Living Operational Model
A shared model of how people, machines, material, movement and space relate over time.
Ops Intelligence
Timelines, patterns and Andy's reasoning that make lost time and capacity easier to investigate, informing decisions rather than commanding equipment.
- Working today
- Functioning software prototypes and demonstrable interfaces, shown with demonstration data.
- In development
- Industrial sensing integrations, factory data collection and broader operational modeling.
- Longer-term research
- Reduced reliance on wearables, camera-free sensing, multimodal sensor fusion and richer spatial intelligence.
Where it's heading
What if the factory itself could sense how work moves?
Today's manufacturing systems can report machine status, production output, and inventory transactions. But many important events happen between those systems: a delayed material delivery, time spent waiting at a workstation, unnecessary travel, or congestion around a production area.
Anderion is investigating how existing operational data, machine signals, and targeted physical sensing can help fill those gaps.
Our longer-term research includes Wi-Fi-based sensing, radar, and other approaches that may provide movement and occupancy information with less dependence on wearable tags or continuous camera coverage.
The goal is to build a more complete understanding of factory activity and connect that spatial context to production performance, historical analysis, and Andy's recommendations.
Camera-free sensing and reliable tagless spatial tracking are research objectives undergoing technical validation.
Future visibility may include
- Movement patterns
- Waiting and dwell time
- Material handoffs
- Repetitive travel
- Factory congestion
- Task context
- Human–equipment interaction
- Physical constraints
- People and autonomous systems working together
As factories become increasingly autonomous, Anderion is being designed to provide shared operational context for people, machines, material and autonomous systems.
Understand the work, not monitor the individual.
The principle guiding Anderion's spatial direction: movement and location insight is meant to answer operational questions, such as where flow breaks down, where waiting builds and which constraints matter most.
About Anderion
Built in Cleveland. Built for the realities of manufacturing.
Anderion was founded on a simple belief: the future of manufacturing will depend not just on collecting more data, but on understanding how people, machines, materials, and processes work together.
Founded in Cleveland, Ohio, by Brandon Anderson, Anderion grew from years spent working alongside manufacturing and healthcare organizations through workforce and staffing operations. Across those industries, the same challenges appeared repeatedly: disconnected systems, inefficient workflows, and valuable information that rarely translated into meaningful decisions.
Those experiences became the foundation for Anderion.
Today, Anderion has built functioning Ops Intelligence software and is preparing for manufacturing pilots. Our broader ambition is to connect operational data with the physical realities of the factory, helping manufacturers understand lost time, identify constraints, and make better decisions about capacity and automation.
We're building toward a future where people, machines, and increasingly autonomous systems can be understood within one connected operational environment.
- Company
- Anderion LLC
- Headquarters
- Cleveland, Ohio
- Stage
- Pre-seed, founder-led
Meet the FounderBrandon Anderson
Brandon's path into technology didn't begin in a software company. It began as a business owner working directly with employers, trying to solve problems that existing tools weren't built to address.
What started as an effort to develop better workforce technology evolved into a much larger ambition: building an industrial intelligence company that could change how manufacturers understand and operate their facilities.
Today, Brandon is building Anderion in Cleveland, drawing on his experience in workforce operations, his perspective as an entrepreneur, and his belief that some of the most important technological advances of the next decade will happen in the physical world.
And that the companies building them don't all have to come from Silicon Valley.
They can come from Ohio.
Pilot program
Start with one part of your factory worth understanding.
We're seeking manufacturing partners to help validate Anderion Ops Intelligence in real production environments. Begin with a defined operational problem, evaluate available data and determine what additional sensing might reveal.
- 1
Define the loss
Identify a recurring production, movement, downtime or capacity problem.
- 2
Connect the evidence
Understand what your existing systems and operational signals already reveal.
- 3
Measure what was previously invisible
Identify missing operational visibility and evaluate where targeted sensing could add useful context.
Request a Manufacturing Pilot
Tell us about your operation. We'll follow up personally.