Defect detection
for live production
Launch inspection in days, not quarters. Start with operator review, then add software or edge integration only where the line demands it.
What We Offer
Off-the-shelf AI & edge integration
Production Defect Detection for Quality Control
An off-the-shelf defect-detection product with defect flags, localization, thresholds, and operator review. Deploy it as a standalone QA workflow, a Docker or ONNX-based service, or an MCP-connected component inside existing reporting and triage stacks.
- Off-the-shelf product, ready to deploy today
- Standalone workflow, Docker or ONNX service, or MCP-connected QA component
- Paid pilot, annual production license, optional edge integration
- Acceptance set on escape rate, false rejects, and line response
On-Edge Hardware Integration
Separate deployment service for teams that need models running directly on production hardware. Millisecond inference, on-prem control, and integration into plant systems.
- Separate commercial package for PLC, HMI, MES, and line triggers
- Deployed and integrated on-site by our team
- Zero cloud dependency, fully on-premises
- 95% to 99% less compute than standard approaches
Deployment and Integration
From review workflow to production control
Standalone Inspection Workflow
Deploy the core product as an operator-facing workflow with defect flags, localization, thresholds, and review queues before you touch machine-side automation.
Software and Agent Integration
For existing QA software, package the core workflow as a Dockerized service, an ONNX-based deployment target, or an MCP-connected component. LabVIEW and test-bench handoff can be scoped where relevant.
Separate Edge Automation Service
When the line needs deterministic machine-side control, the separate On-Edge Hardware Integration offer handles PLC, HMI, MES, and trigger wiring on site.
Full Stack
Core capabilities
Technical FAQ
For the Engineers & Scientists
Get Started
Take defect detection into production
Start with a paid pilot on your own imagery, deploy the approved inspection as a standalone workflow, Docker or ONNX service, or MCP-connected QA component, and add edge integration only where machine-side automation is required.
Got a problem but
no data?
No dataset, no infrastructure, no problem. We build custom AI solutions from scratch, from data collection to model deployment. If it can be solved with AI, we'll find a way.