Most Enterprise Video is Recorded and Never Watched. Put It to Work, Governed.
Manufacturing facilities, logistics hubs, and regulated sites collect thousands of hours of video that sit on DVRs and go unreviewed. CreateOS forward-deployed engineers turn that footage into governed operational intelligence: defect flags, safety alerts, compliance records, and audit trails that run on-prem or at the edge, with a human in the loop at every step.
- ISO 27001 and SOC 2 Type II certified
- On-premise or at the edge
- Human in the loop
- Governed and auditable by default
The Gap is Production, Not the Camera
Video runs constantly and goes unreviewed. Point tools stop at detection and ops tools stop at alerting. CreateOS unifies ingestion, detection, governance, privacy masking, and audit in one path, which is what closes the gap.
of enterprise AI pilots never reach production.
MIT NANDA, 2025
hours of CCTV footage processed across 75 days in an Indian textile pilot, with no in-house DevOps team required.
CreateOS Industrial AI Pilot, 2025
of new cyber-insurance now excludes ungoverned AI risk.
Munich Re, 2026
What We Deliver
Computer vision built for production from the first camera feed, not a demo that stalls at the security review.
Video and image intelligence
We ingest your existing camera feeds and image archives, index them, and make them searchable and actionable in a governed workspace, no rip-and-replace hardware required.
Defect and quality inspection
Real-time detection of defects, deviations from standard, and out-of-spec items on the production line. Every flag is logged with the frame, timestamp, and a link to the source.
Safety and compliance monitoring
Watch for safety conditions, PPE compliance, and restricted-zone access across your floor. Personal data is masked before any output. Alerts go to a person before any action is taken.
Edge and on-prem deployment
Models run where your cameras are: on-prem in the facility, at the edge without a cloud dependency, or hybrid. Footage never leaves the environment you control.
Human-in-the-loop review
Every flag, alert, and decision routes to a person before it touches a workflow. Approval gates and escalation paths are configured to your operations, not a vendor default.
Governance and audit trail
Every inference is logged with the frame, the model version, the decision, and the reviewer action. A compliance or operations team can inspect any event end to end.
How an Engagement Works: The Production Path
A staged path from concept to governed production. Value lands early and governance holds at every step.
- 01
Discover
We map your existing cameras, footage, and operational pain. We pick the highest-impact CV use case, scope it, and produce a build spec and production roadmap. Fixed pricing agreed in writing.
- 02
Prove
We run a scoped pilot on your own video data, governed from the first frame, to prove detection accuracy and operational value against real footage from your environment.
- 03
Productionize
Forward-deployed engineers harden the system: edge or on-prem packaging, privacy masking, alert routing, human-in-the-loop gates, and a full audit trail.
- 04
Scale
It goes live, then spreads. Model lifecycle management, camera expansion, monitoring, and continuous improvement on the governed layer you keep.
Proof: industrial computer vision in production
Over a 75-day pilot, cotton processing facilities across Maharashtra, Tamil Nadu, Telangana, and Gujarat connected their existing CCTV systems to CreateOS. The pilot converted passive footage into active operational dashboards with traceability and accountability records, with no in-house DevOps team and no new camera hardware required. Forward-deployed engineering on the governed execution layer, running at the edge in each facility.
Hours of CCTV footage ingested, indexed, and made searchable across the pilot.
Total footage processed into a unified governed workspace with no on-site DVR risk.
Pilot duration across four Indian states, from first camera connection to operational dashboards.
Computer Vision We Put into Production
Governed detection and monitoring systems taken live on the execution layer, each with a human in the loop and a full audit trail.
Fabric defect detection
Spots fabric defects on the line in real time and logs each flag with an image for the quality team to confirm. Bad rolls are caught before they reach customers.
Visual quality inspection
Checks products against your quality standard, flags what is out of spec, and routes it for review. Every decision is recorded with the frame and the reviewer action.
CCTV compliance monitoring
Turns existing CCTV into governed, real-time compliance oversight. Personal data is masked before any output, and every event is logged for audit.
Worker-safety monitoring
Watches for safety conditions, PPE compliance, and unsafe behavior on the floor. Alerts go to a person in real time, with personal data masked throughout.
Restricted-zone access control
Detects unauthorized access to restricted areas and logs each event with the timestamp and camera. Alerts route to security before any action is taken.
Shade and color matching
Checks each production lot against the color reference and flags lots that drift out of tolerance, with the comparison image and lot record preserved for QA.
Machine and loom monitoring
Watches machine state across the floor, surfaces stoppages and faults as they happen, and keeps a record the operations team can act on.
Video archive intelligence
Makes legacy footage searchable and actionable. Index hours of archived video so incidents, compliance events, and operational patterns can be found without manual review.
Provenance and traceability records
Builds time-aligned visual records of key production areas, ready to share with buyers or auditors. Verified by the same footage your cameras already capture.
Why CreateOS for Computer Vision
Governed from day one
Privacy masking, audit trail, and human-in-the-loop gates are on from the first camera feed, not added before the compliance review.
Engineers who ship onto a platform you keep
Forward-deployed engineers embed with your team and ship onto the unified AI execution layer we operate. The engagement ends; the governed layer stays.
Runs where your cameras are
On-prem, at the edge, or hybrid. Models run in the environment you control. Footage never crosses a boundary you did not approve.
You own everything
All models, pipelines, code, and IP are yours outright. We document everything and train your team to manage what has been built.
Common Questions
What does a computer vision engagement with CreateOS cost?
Engagements run on fixed-scope pricing, not hourly retainers. A discovery sprint and first pilot scope is agreed in writing before any build begins. Cost depends on the number of camera feeds, detection complexity, deployment mode, and integration depth.
How long does it take to get computer vision into production?
The standard rollout is 12 weeks across three gated phases. The fastest comparable deployment went from first camera connection to live operational dashboards in 75 days. Simpler use cases can go live in under four weeks.
Can you deploy on-premise or at the edge?
Yes. That is the most common configuration for manufacturing and industrial deployments. Models run where your cameras are: on-prem in the facility, at the edge without a cloud dependency, or hybrid. Footage never leaves the environment you control.
How is video data and footage protected?
Footage is processed in your environment with region-locked compute and zero data retention by default, so it never crosses a boundary you did not approve. Personal data is masked before any output reaches a user or downstream system.
Who owns the models and IP after the engagement?
All models, detection pipelines, code, and IP are yours outright. We document everything and train your internal team to manage what has been built.
How accurate are the detections, and what about false positives?
Accuracy depends on the use case, lighting, camera placement, and training data. We measure baseline performance on your own footage before the pilot and agree on accuracy targets in writing. Every flag routes to a human reviewer, so a false positive does not trigger an automated action.
Can we use our existing cameras and footage?
Yes. We work with whatever camera infrastructure you already have, including legacy CCTV systems. Existing footage archives can be indexed and made searchable without re-ingesting from new hardware.
Where do you want to start?
Bring one camera feed or video archive. We will turn it into governed operational intelligence.