Talk through your design.
Catch what you missed.
Talk through your design with an AI that listens like an engineer. It captures your decisions, flags gaps at the boundaries, and tracks what you decided, why, and what depends on it.
You
I need a drone that can carry 5 kg within a 2-mile radius.
Co-pilot
What's the payload, and what's the mission? Delivery, equipment mounting, or sensor packages — those drive fundamentally different designs.
You
Surveying agriculture fields. Thermal imaging.
Co-pilot
Thermal cameras in this class typically weigh 150–200g — your 5 kg spec may be 25x above what you need. And a 10-acre field is ~200m across, well within a fraction of your 2-mile range. Worth starting from the actual mission parameters?
You know your components.
You're missing the spaces between.
Engineers think one component at a time. Failures live in the connections — where the battery meets the motor, where the sensor talks to the MCU, where firmware assumes a voltage the hardware doesn't deliver.
A typical cross-domain system has dozens of these boundaries. Engineers define 2–3 parameters at each one. The other 4–5 surface at integration — when fixing them costs $5K–$50K and 6 weeks.
The co-pilot catches those gaps while you're still talking.
We're not a PLM. Not replacing your CAD or BOM tool. We're the thinking layer before all of that — where decisions get made and where the expensive mistakes happen.
Think out loud. Get structured output.
Step 1
Describe your project
Talk about what you're building in plain language. No forms, no modeling syntax, no "shall" statements.
Step 2
The co-pilot sharpens and captures
It asks the questions your design review would ask — but earlier, and without missing anything. Vague specs get sharpened. Premature decisions get challenged. Dependencies get tracked.
Step 3
Your decisions, structured
Every decision tracked with specs, rationale, and dependencies. Change one thing — see what else is affected.
One sentence — "a touchless thermometer for children" — becomes testable decisions in four exchanges:
| Decision | Spec |
|---|---|
| Measurement accuracy | ±0.5°F (±0.28°C) across 95–104°F |
| Measurement time | Complete reading in ≤3 seconds |
| Target mode | Forehead (non-contact) |
| Test protocol | Calibrated reference at 98.6°F, 100.4°F, 102°F |
Real session, 3 minutes in. Engineer said 6 words. Co-pilot captured 2 testable decisions:
You
I want to create a touchless thermometer for children.
Co-pilot
What problem are you trying to solve? Is this for home use, clinical settings, or something else? And what does success look like — parents checking fever at bedtime, or nurses triaging 50 kids/hour?
You
Within ±0.5°F, toddler squirming but cooperating for 2–3 seconds.
Co-pilot
Decision 1: Measurement Accuracy ├─ Spec: ±0.5°F (±0.28°C) across 95–104°F range ├─ Test: Calibrated reference vs device on water bath at 98.6°F, 100.4°F, 102°F └─ Status: Captured Decision 2: Measurement Time Window ├─ Spec: Complete reading in ≤3 seconds from trigger ├─ Test: Stopwatch from button press to displayed result, 20 trials └─ Conditional: Assumes forehead aim (not ear canal)
Caught before hardware.
An engineer specified 7-inch propellers for hover efficiency on an agricultural drone. Another specified a 250mm folding frame to fit a Pelican case. Both choices correct in isolation.
Co-pilot
Frame arm length: ~125mm. Prop radius: 89mm. Clearance between adjacent props: 6mm. 6mm is below the 15mm safety minimum. At flex and vibration — props will collide.
Neither made a mistake. The conflict only exists at the intersection.
| Without co-pilot | With co-pilot | |
|---|---|---|
| When discovered | Assembly (week 6) | Conversation (minute 15) |
| Cost | ~$2K + 3 weeks | $0 + 30 seconds |
Real engineering artifacts. Not chat logs.
Generated from your conversation. Structured. Searchable. Ready for design reviews.
Decision Document
Every decision with specs, rationale, rejected alternatives, and dependencies.
Interface Control Document
Every boundary where responsibility transfers — connectors, signals, data formats, thermal paths.
Dependency Map
What connects to what, and what breaks when something changes.
This isn't ChatGPT with an engineering prompt.
ChatGPT can answer engineering questions. It can't track 30 decisions, flag when decision #27 contradicts decision #4, or catch that two engineers made independently valid choices that are physically incompatible.
The co-pilot doesn't make decisions. You do. It asks questions, flags gaps, and surfaces conflicts. You verify and decide.
If your system crosses domains, this is for you.
Built for projects where mechanical, electrical, and software interact — drones, robots, medical devices, anything with 10+ components that talk to each other.
"I had the props and frame specced on the same page and still missed it. The co-pilot caught that my 7-inch props left 6mm clearance on a 250mm frame — they'd clip in any crosswind. That's a $2K carbon fiber reorder I didn't have to make."
— Drone engineer, agricultural survey project
"I said 10 pounds max and 12-hour runtime in the same breath. Seemed reasonable. The co-pilot did the math I hadn't — the battery alone could weigh 10 pounds. I would have gotten to prototyping before realizing the weight budget was broken."
— Embedded systems engineer, roadside safety device
"I didn't realize the motor change affected the thermal budget until the co-pilot showed me. I would have found that at integration — three weeks and a board respin later."
— Hardware engineer, validation session
Try it on a real project.
First session
Free
After that
$29
per month
One session. One project. $29 per month.