Scan one reference board
From one board of the current batch, AI learns component positions and appearance — no CAD, no defect library.
Inspection · AI AOI Software · SOFTWARE
DaoAI AI AOI Software — built on a visual foundation model with feature cognition; model from one good sample. No CAD, no defect library, 100% on-premise, and embeddable in any 2D / 3D equipment.
From one board of the current batch, AI learns component positions and appearance — no CAD, no defect library.
Locates components, pins and polarity in seconds; handles rotation, flips and same-color parts — no hand-drawn ROIs.
Thresholds are derived from the board so operators can run it, and accuracy improves with every piece of feedback.
Understands a component's "identity" rather than comparing pixel and color similarity.
Black parts on a black board, silver traces and silver parts — same-color scenes separate naturally in feature space.
Precise localization despite rotation, flips and surface contamination.
An inspector labels a false call once, the model updates, and the same error never recurs.
Tells acceptable process variation from real defects; false calls keep falling with feedback.
Continuously optimized for your products and defects, becoming a dedicated model that grows stronger the more you use it.
Flexible Deployment · DEPLOYMENT
Embed into your existing AOI / vision equipment and line software.
Standard interfaces connect to MES / host systems, with results flowing back in real time.
One-click private deployment — isolated environment, easy to operate and maintain.
Works out of the box with DaoAI 2D / 3D equipment.
Weights and data stay 100% inside the factory — secure and compliant.
<12ms on-premise inference — no cloud needed, works offline.
DEFECT COVERAGE
| Criteria | Traditional rule-based AOI | Generic AI AOI | DaoAI Software |
|---|---|---|---|
| Inspection paradigm | Color / template matching | Generic classification network | Visual foundation model · feature cognition |
| Modeling data | Manual rules | Thousands of defect images | One good sample |
| Programming time | 3–5 hrs per board | Depends on AI engineer | Operator finishes in 5 min |
| Optimization | Fixed algorithm | Requires vendor retraining | Learns and updates from line feedback on the spot |
| Deploy | Locked to dedicated hardware | Often needs the cloud | SDK/API/Docker · 100% on-premise |