Agrani · evidence pendingComputer Vision Quality Inspection Agent
Inspects parts on the production line via cameras and computer vision models trained on defect imagery. Typical impact reduces escape defects by 15-25 percent and inspection labor by 50-70 percent.
Workflow
Where it sits on the operating loop
Every Wayam solution is composed across four responsibilities. This agent's primary job is Act and it touches Reason. Autonomy is draft-then-approve: a named owner signs before anything writes back.
Systems of record
Reads from
- Cognex VisionPro
- Siemens MES MCP
- NVIDIA Jetson
01
Ingest
Connect the systems above and read the signals the work already produces.02Touches
Reason
Ground context, score options against policy and the goal, draft the next step.- YOLOv8
- fine-tuned ViT-L
Gate · draft-then-approve
Manufacturing Operations signs
Approves, edits or rejects the draft. Nothing writes back without a name on it.
reject returns to 02
03Primary
Act
Execute the approved step in the system of record and keep the evidence.Systems of record
Writes back to
- Cognex VisionPro
- Siemens MES MCP
- NVIDIA Jetson
The run above is the shared Wayam pattern drawn with this agent's own systems, models and owner; the workflow specific to your estate is drawn in discovery. Architecture view: L6 · Execution, touching L5.
Typical user
Manufacturing Operations lead
Typical owner
Manufacturing Operations
What it does
- Detects defects in manufactured parts using camera-based inspection.
- Human review sits on the write-back, not on the research.
- Evidence of every draft, approval, and action is kept with the record.
Evidence
What Wayam can show for this entry
Agrani · evidence pendingCurated solution design with an owner and a review date. No performance or production claim.
Allowed claims at this tier: Possible workflow, typical stack, prerequisites.
- Evidence tier
- T4 · Reference pattern
- Integration status
- Not yet specified
- Metric status
- Scenario only
- Evidence owner
- Not yet attached
- Validated
- Not yet attached
- Valid until
- —
- Content version
- 2026.09
Agrani slot: Visual defect detection
Bundle manufacturing-energy. Owner: not yet assigned. Evidence due: not yet scheduled.
Agrani marks the thirty capabilities Wayam is prioritising for a run replay, an evaluation set and a validation date. Until those are attached this entry is still a reference pattern.
Pending evidence attachment
This entry represents an enterprise architectural reference pattern. Customer benchmarks, run replays, and metric verifications are established during technical discovery.
Limitations
- Systems and models listed are a typical stack, not a tested integration.
- ROI bands are directional and carry no customer measurement.
Verified run replay
trc_eye_20260911_33b55Environment: Wayam test environment (verified replay)
- cameraFeed:
- Conveyor Station #4 (High-Speed Industrial CMOS)
- partType:
- Automotive Transmission Gear (Forged Alloy Steel)
- lineSpeed:
- 1.2 parts/sec
Input classified & sanitized
ZDR boundary verifiedWayam Eye Vision Model v2.8
Latency: 420ms2 tool actions executed
Status: All successPolicy cleared
autonomous_action_executedAutonomous physical rejection gate with real-time PLC trigger (< 50ms requirement)
Architecture & controls
How it is governed and what it connects to
Control gates
- Manufacturing Operations approves, edits or rejects before any write-back
- Evidence of every draft, approval and action is kept with the record
- Data residency: on-prem, edge
- Role-based access on every connector; the agent reads before it writes
What must be in place first
- A named business owner with the decision right to approve this agent's output
- A system of record the output lands in, with read access and a scoped write path
- A measurable baseline: volume, handling time, error or rework rate
- Sample records or transcripts that can be shared, redacted where required
Typical enterprise systems
Not yet specifiedTypical stack for solution design; compatibility is validated during discovery.
- Cognex VisionPro
- Siemens MES MCP
- NVIDIA Jetson
Model options
Models the platform can route to. Listing one does not mean this agent has been tested with it.
- YOLOv8
- fine-tuned ViT-L
Business case
Model a scenario with your own baseline
Three scenarios from the numbers you enter. Capacity released is time; it becomes a saving only when roles or costs are actually removed or avoided.
Improvement is seeded at the midpoint of this entry's directional band (20–40%). Source status: scenario only. Edit it to your own estimate.
| Scenario | Improvement | Capacity released | Cashable savings | Net annual | Payback |
|---|---|---|---|---|---|
| Conservative | 11% | — | — | — | — |
| Expected | 21% | — | — | — | — |
| Upside | 29% | — | — | — | — |
Enter an annual volume and a baseline cost to see figures.
Illustrative planning scenario, not a guarantee. Results depend on process baseline, adoption, data quality, integration scope, controls, and deployment costs.
Pilot this
From reference pattern to a bounded pilot
Nothing on this page is a commitment. The path is a short discovery to validate the workflow and baseline, then a pilot with acceptance criteria agreed up front.
Step 1 · 3–4 weeks
Discovery Sprint
Validate the workflow, data, controls, baseline and business case before anything is built.
Gate: Blueprint and pilot plan signed by the business owner, technical owner and Wayam.
Step 2 · 6–10 weeks
Bounded Pilot
Prove quality and value on agreed data against agreed acceptance tests.
Gate: Acceptance thresholds met on the evaluation set; go/no-go decision recorded.
What happens next: a Wayam owner connects within 1 business day to schedule a 30-minute review of fit, prerequisites and scope.
Similar patterns
Similar patterns
AGT-0201·Computer Vision Quality Inspection Agent·T4