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
The AI inspection brainthat programs itself in 5 minutes.
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.
SOVEREIGN AI VALUE
Your process know-how never leaves your line.
Yield curves, defect signatures, process parameters — this is a factory's core trade secret. Under IDC's framework, the AI inspection brain starts with data sovereignty: flexible SDK / API / Docker deployment, with sample images, results and model weights never leaving your site or training any third-party model.
- Process parameters stay yours
Good-sample templates and defect libraries are decades of production know-how — we help you use it, never help anyone else learn it.
- <12ms edge inference, works offline
Core inspection logic runs on the line itself, independent of external networks or cloud availability.
- A model that only gets smarter for you
Line feedback keeps refining your own private model — the edge you build stays yours, not a shared foundation.
5minto program & deploy (was 3 hrs)
1Model from one good sample
99%+detection accuracy
−80%false-call rate
1M++real training images
100%On-premise · data stays on-site
AI maps components automatically
Locates components, pins and polarity in seconds; handles rotation, flips and same-color parts — no hand-drawn ROIs.
AI derives thresholds
Thresholds are derived from the board so operators can run it, and accuracy improves with every piece of feedback.
Feature Cognition
Inspect in feature space, not color space- Pre-trained on millions of components
Understands a component's "identity" rather than comparing pixel and color similarity.
- No more false calls on same-color parts
Black parts on a black board, silver traces and silver parts — same-color scenes separate naturally in feature space.
- Any orientation · contamination-resistant
Precise localization despite rotation, flips and surface contamination.
Sharper over time · data loop
Every piece of feedback makes the model smarter- Learn and update on the spot
An inspector labels a false call once, the model updates, and the same error never recurs.
- Semantic-level false-call filtering
Tells acceptable process variation from real defects; false calls keep falling with feedback.
- Building data assets
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
Missing / wrong partTombstonePolarity / flipSolder bridgeMisalignmentOCR charactersForeign objectInsufficient solderContamination / debrisDIP solder-joint class
| 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 |
FAQ
What data is needed for the 5-minute automatic programming AI quality inspection brain to build a model?
DaoAI's 5-minute automatic programming AI quality inspection brain is based on the feature recognition of the visual foundation model. It can build a model with just one good sample. No CAD or defect sample library is required. It's simple and efficient, and can be quickly put into use.
What are the advantages of this quality inspection brain compared with traditional rule-based AOI?
Compared with traditional rule-based AOI, our quality inspection brain uses the feature recognition of the visual foundation model. It can complete programming in 5 minutes with one good sample, while the traditional method takes 3-5 hours per board. Also, our model can be continuously optimized and becomes more accurate over time.
Can this quality inspection brain be deployed flexibly?
Yes. It supports various deployment methods such as SDK integration, REST API standard interface docking, one-click private deployment in Docker containers, and out - of - the - box use with local all - in - one machines. Data stays 100% in the factory, and edge inference is <12ms, available even offline.
The Q&A above was generated with AI assistance and is for reference only; official specifications and commitments are subject to direct consultation.