Talk about AI in 2026 and nine times out of ten it's about AI agents — from coding and slides to support, research and sales. But when that agent wave hits the hardest industrial floor (SMT lines, PCBA inspection), it goes almost silent.
The reason is simple: a production line doesn't want a model that can chat.
A line doesn't need a chatty LLM agent — it needs millisecond, deterministic visual judgment that runs locally.
Put a GPT-scale model on an AOI to call a missing part? The latency won't allow it, the cloud won't allow it, and false calls certainly won't allow it. But that doesn't make the agent era irrelevant to industrial AI — quite the opposite. The real revolution of agents isn't "how big the model is," but the design philosophy: goal-centered, a perceive-decide-act-reflect loop, and freeing humans from writing rules toward "giving intent and feedback."
What DaoAI does is bring that agent design philosophy into PCBA visual inspection. Our core isn't a large language model but a visual foundation model trained for SMT; yet the underlying workflow — auto-generating inspection regions, auto-generating inspection logic, learning from operator feedback, iterating the model — is pure agent thinking. This June, that answer travels to Taipei.
Why CTA? Why Taipei?
DaoAI will join the Canadian Technology Accelerator (CTA) Hard Tech Cohort alongside seven other Canadian companies at Computex InnoVEX 2026 in Taipei, exhibiting in the Canada Pavilion.
CTA is a flagship global accelerator led by Global Affairs Canada, open only to internationally competitive "deep-tech" companies and built to help them enter the world's most critical industrial clusters. In CTA's global map, Taipei's role is clear: a key hub of ICT and hard tech (semiconductors / SMT / robotics). From advanced packaging to PCBA assembly, this is not just a production base but the proving ground for industrial AI.
DaoAI is the only company on this list whose core technical thread is "deploying AI visual inspection."
Bringing the agent design philosophy into AOI
Traditional AOI is a classic "rule engine": engineers manually draw regions, tune parameters and write judgment logic, taking 3–5 hours for every new board — humans enumerate every rule, the machine only executes. The paradigm shift agents bring is to flip that relationship: humans give goals and feedback, and the AI decides how. DaoAI lands this on the line at four levels:
① Goal-driven: give it a reference board, not a rulebook
- AI automatically recognizes every component on the board
- It computes each component's judgment threshold from the good parts
- It auto-generates inspection regions
- New-board programming in 5 minutes, changeover time cut by 97% — no CAD, no component library, no AOI engineer
② Perceive-decide-act-reflect: a closed loop on the line
- Perceive: a visual foundation model trained on 1M+ real SMT images extracts multi-dimensional features in 1ms/component — not by RGB comparison, so it solves long-standing problems like same-color parts, SOD/LED polarity, and black-inductor character interference.
- Decide: a single frame judges missing/wrong/misoriented/reverse-polarity parts, tombstones, physical damage, surface scratches, foreign-object contamination and DIP solder-joint quality, at ≥98% accuracy.
- Act: defect data is pushed in real time via MES API, SPC trend reports are generated automatically, and the line can react immediately.
- Reflect: every operator review feeds back into the model; false calls fall 80% vs. traditional AOI and keep dropping over time — it gets sharper the more you use it.
③ Data sovereignty: the agent runs locally, the model never leaves the plant
One of the biggest limits of a general LLM agent is that data must go to the cloud. For EMS / OEM that path is a non-starter — BOM structure, defect distribution and process parameters are all trade secrets. DaoAI's answer is 100% on-premise: training, inference, judgment and SPC all run locally and data never leaves the plant, while keeping millisecond response in any network environment.
④ Turn people from "writing rules" into "giving intent and feedback"
The modeling work that once required a senior AOI engineer can now be done independently by a line operator after brief training — humans step back to "set goals, review," and AI takes over everything that can be automated. The result: about USD 15,000–40,000 saved in labor per person per year, and 60% lower overall operating cost.
Not just a machine: a full product line × an extensible platform
DaoAI's AI-AOI isn't a standalone device but an intelligent inspection platform that embeds deeply into existing MES / SPC systems:
- Hardware: the PCBA 2D AOI family — P1 (offline standard), P2 (12MP / 10μm high precision for QFN / BGA / CSP, medical, aerospace), P3 (single-track inline), P3D (dual-track inline for high-throughput plants); a 3D version (S1-500D) is coming.
- Integration: MES connectivity, built-in SPC trend reports, browser-based remote review, and offline pre-programming (new models prepared without interrupting the live line).
See you in Taipei this June
- June 2–5: Computex InnoVEX 2026, on the show floor
- Location: Taipei Nangang Exhibition Center Hall 2 (TaiNEX 2) · Canada Pavilion
- On site: product walkthroughs, customer case sharing, 1-on-1 technical consultation, and booking follow-up factory validation
We're looking for SMT equipment agents / distributors (bring "AI programming, 5-minute changeover" to your customer network), AOI system integrators / OEMs (model licensing, OEM integration and co-development), and EMS / OEM line managers who want to cut changeover time by 97% and review labor by 80%.