Edge AI inspection for mobility and manufacturing lines.
Chitti.AI helps factories detect weld, paint, battery-pack, chassis, packaging, and supplier-part defects in real time using edge-deployed computer vision.
Start with one line. Prove one defect class. Scale across plants and suppliers.
Factory quality is still too manual for modern production speed.
Defects escape the line
Visual inspection depends on operator attention. Fatigue, shift changes, and high line speed mean defects are missed consistently.
Inspection data is fragmented
Paper logs, Excel sheets, and disconnected systems make it impossible to track quality trends across shifts and lines.
Supplier visibility is weak
Incoming quality data stays at the receiving dock. No centralized view of supplier defect patterns or part-level trends.
Cloud-only AI breaks on factory floors
Unreliable internet, high latency, and data privacy concerns make cloud-dependent inspection impractical for production environments.
Real-time inspection intelligence on the production line.
From image capture to actionable quality intelligence — every inspection writes a traceable, auditable record.
Built for high-variance industrial inspection use cases.
Weld and Chassis Inspection
- Weld gap
- Porosity
- Undercut
- Bead irregularity
- Surface crack
EV Battery Pack Inspection
- Seal damage
- Connector misalignment
- Cable routing error
- Label mismatch
- Enclosure scratch
Paint and Surface Inspection
- Scratch
- Dent
- Coating defect
- Dust particle
- Color mismatch
Supplier Incoming Quality
- Part damage
- Wrong label
- Missing marking
- Dimensional visual anomaly
- Packaging damage
Packaging and Label Verification
- Missing label
- Wrong batch code
- Label skew
- Seal issue
- Barcode mismatch
Service/Warranty Image Triage
- Visible damage
- Part mismatch
- Accident evidence
- Claim image inconsistency
- Surface defect
Built for factory floors, not data centers.
Low Latency
Inference runs locally on edge devices — ~200ms per inspection. No round-trip to the cloud.
Offline-First
Inspection continues even without internet. Results sync when connectivity is available.
Lower Deployment Cost
Runs on affordable hardware — Raspberry Pi, Jetson Nano, or existing shop-floor cameras.
Factory Data Control
Inspection images and records stay on-premise. Only encrypted quality summaries leave the facility.
Flexible Capture
Works with phone cameras, USB cameras, IP cameras, or integrated edge device cameras.
Traceability & Reports
SHA-256 audit chain, pilot reports, and exportable compliance records for every inspection batch.
Beyond detection — a quality intelligence layer for your factory.
Vision Models
Trained on your defect classes, deployed to edge devices.
Inspection Records
Every inspection creates a traceable, timestamped record with image evidence.
Operator Decisions
Operators confirm or override detections — human-in-loop is mandatory.
Supervisor Alerts
Real-time alerts for defect clusters, shift trends, and threshold breaches.
Quality Dashboards
Defect trends, line performance, supplier quality, and inspection metrics.
Traceability & Reports
SHA-256 audit chain, pilot reports, and exportable compliance records.
Deployment Plan
One line. One defect class. One measurable quality metric.
Line Selection and Data Capture
Identify the target line and defect class. Capture representative good and defective samples.
Defect Taxonomy and Annotation
Label and classify defect types. Build the ground truth dataset for model adaptation.
Model Adaptation and Edge Setup
Fine-tune detection model. Deploy to edge device on the factory floor.
Shadow Mode
Run parallel with existing QC. Compare detections. Measure false positives and misses.
Dashboard and Alert Validation
Validate dashboards, alert thresholds, and operator workflows with real production data.
Pilot Report and Scale Recommendation
Deliver pilot results, quality metrics, and recommendations for production rollout.