Help students fix lab setups, without giving away the answer.
BridgeLab AI looks at a photo or short video of an electronics or robotics build, spots likely mistakes, and coaches the student in Arabic or English with hint-first guidance.
Designed for STEM classrooms where teachers can't be at every bench at once.
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BridgeLab AI
Detected issue
LED wired without a current-limiting resistor.
Hint, not the answer
Apply Ohm's Law with Vs=5 V, Vf=2 V, Iā10 mA. What value of R falls out?
The problem
The bench is busy. The teacher is one person.
In a real STEM lab, twenty students hit small wiring or component mistakes at the same time. They wait, they guess, or they get the answer dumped on them. BridgeLab AI gives every student an Arabic-English coach that explains what's wrong and asks the next right question.
Features
What it does
Detects likely setup mistakes
Identifies common wiring, polarity, and pin-assignment errors from a single photo or short clip.
Explains in Arabic or English
Full bilingual interface with proper RTL layout, not a half-translated tool.
Hint-first learning
Returns a guided hint and a follow-up question instead of dumping the full solution.
Teacher class insights
Aggregates anonymous results into a dashboard of common errors and learning gaps.
Safety-aware feedback
Flags wiring issues that pose burn-out, short-circuit, or sudden-motion risks before the student powers on.
Pipeline
How it works
From the photo on the bench to the teacher's dashboard, in five steps.
1. Student uploads
A photo or short video of the build is captured on a tablet or phone, locally.
2. Component detection
A vision model identifies the components on the bench: board, LED, resistor, sensor, driver, jumpers.
3. Rule-guided inference
Detected components and their relationships are checked against a library of common lab mistakes.
4. GenAI explanation
A language model writes a short, age-appropriate explanation in Arabic or English from the structured diagnosis.
5. Hint-first pedagogy
The response is shaped as a hint plus a follow-up question instead of a full solution.
6. Teacher analytics
Anonymous diagnoses are aggregated into class-level errors, safety alerts, and intervention suggestions.
Responsible AI
Responsible AI by design
Five commitments that shape how BridgeLab AI behaves in a real classroom.
Hint-first, not answer dumping. Students still have to think.
Teacher remains in control. Decisions stay with the educator.
Minimal student data. No accounts, no PII, history stays local.
Designed for safer lab sessions by surfacing safety-relevant issues first.
Class-level insights, not student surveillance.