Berlin · Pre-seed · 2026
cscope
The AI copilot for hardware bring-up & debug.
It reads your schematic, firmware, and bench instruments at the same time, so a new board comes up in hours instead of weeks.
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01 - The problem
Bringing up a new circuit board is still a manual, undocumented guessing game.
When a freshly assembled board hits the bench, a senior engineer ($150 to $300/hr, fully loaded) has to reconcile three things in their head:
Schematic & BOM
what it should do
Firmware
what it's trying to do
Bench instruments
what it's actually doing: scope, logic analyser, DMM, power supply
No tool holds all three at once. So the engineer works it out by hand, and the only record survives like this:
"9 out of 10 times, someone snaps a pic with their phone."
- Time
- Bring-up is the most expensive bench time you'll buy, and it gates every stage of development.
- Knowledge loss
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"Single source of truth is the biggest, biggest problem in embedded/hardware products."
- Handoff tax
- A board handed to another engineer, or picked up again after three weeks, has to be understood from scratch.
02 - Why now
Three things became true in the last 18 months.
The capability and the appetite arrived at once.
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1
AI can finally reason over messy hardware data. LLMs can now read datasheets, schematics, and instrument traces together. Proof it works: an Amazon EE lead built an internal design-checker and injected dozens of errors. Properly guided, a frontier model caught 100%.
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2
AI can now operate the bench, not just read it. Agentic tool use almost always points at software tools (MCP servers, APIs). We point it at physical instruments (scope, logic analyser, power supply), driven in a loop against the live PCB with captures read back.
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3
Engineers actually want AI in their workflow now. Eighteen months ago, using AI at work was a novelty. Now it's expected, and teams are actively hunting for the next job to hand it. The appetite, and the budget behind it, arrived before anyone built the tool that fits the bench.
The plumbing exists, the AI is good enough, and nobody has wired them together for the engineer at the bench.
03 - The solution
The one place that holds your design and your measurements, and reasons across both.
You connect your project (schematic / BOM / firmware) and your bench. Then the agent does what a senior EE does, only faster:
Design-aware debugging
"This rail should be 3.3 V ±5% per your schematic, but the DMM reads 3.8 V, so check R47 and C23." It knows the intent, so it knows when reality disagrees.
Cross-instrument correlation
Scope + logic-analyser + DMM + PSU, lined up against the design and firmware state, automatically, instead of eyeballing four screens.
A journal that writes itself
Every probe, reading, and conclusion captured as a searchable, time-stamped record. That record is your handoff doc and your compliance artifact, for free.
It runs alongside Altium, KiCad and Cadence rather than replacing them. We read your design files, so you never switch CAD tools.
Reliability is verifiable. Our output is checked against an instrument reading, so right or wrong is measurable.
No rip-and-replace. Zero switching cost is the entire adoption strategy.
Cross-vendor by design. Keysight, Tektronix, Siglent, Rigol, Saleae: one agent across all of them.
04 - Founder-market fit
For 15 years I've either been at this bench myself or leading the teams doing the work.
Tom Elliot - Founder
- Built the industry's first all-day, wrist-worn heart-rate sensor at Fitbit, the lowest-power PPG sensor of its time. I took it from R&D to the factory line in the Fitbit Surge, and was Sensor Systems Lead for the Fitbit Ionic. I've lived hundreds of hours of the bring-up and debug pain this solves.
- Led hardware teams from IoT to industrial products: Head of Hardware Engineering at INFARM, Head of Engineering at Senic. Coached teams to ship reliably. I know how hardware orgs work, and how they buy.
- Bootstrapped B2B SaaS for 3 years, with a consistent income stream the last 18 months. I've honed product, sales, and software-engineering chops the hard way.
Domain credibility customers trust on day one
I've sat where my users sit. They open the door because I speak their language, not because I'm pitching them.
I run the company the way the product thinks
AI-native by design. Agents already do the work a team would. Smallest possible team, compute over headcount.
05 - Validation / traction
The pain is real, the buyers are senior, and the pull is already there.
From the bench (customer discovery)
Proof the approach works
The same Amazon signal from Why Now, now with money behind it: its EE lead won VP-level budget to build the design-checker in-house. Big companies are validating the thesis with their own money.
06 - Market
We sell time back to the most expensive engineers in the building.
Bottom-up logic (the number that matters)
- • A senior EE costs $150 to $300/hr fully loaded.
- • Bring-up & debug is a gating, weeks-long step on every board revision; the early revs alone run 20 to 40 hours each.
- • Across a year that's a few hundred senior-EE hours, or $25k to $90k of one engineer's time, in a phase with no dedicated tool.
So the wedge ACV is a per-seat number anchored to that labour, not to a CAD licence.
Beachhead
Well-funded robotics & hardware startups (Foundation, Bedrock, Mytra, et al.) and product teams / consultancies shipping in a hurry. They feel bring-up pain weekly and move fast on tools.
Expand
The broader installed base. The EDA tools market alone is ~$10B/yr (Altium plus Cadence), on top of a ~$40B engineering-tools market. Not a TAM claim, just the direction once the wedge lands.
A growing market: AI means more new hardware products, built faster by leaner teams. More boards to bring up is our tailwind.
07 - Competition & differentiation
The AI-EDA wave is real, and it's all aimed at designing the board. Nobody is at the bench after it's built.
Prompt-to-hardware (for beginners)
Schematik ($4.6M pre-seed), Atech ($800K pre-seed)
Plain-English idea → first prototype
Not us: built for people who don't know what a resistor is; idea→prototype, not bring-up
Physics-driven layout
Quilter ($40M; traction)
Autonomous PCB placement & routing
Not us: pre-fabrication design; not bring-up
Browser AI copilots
Flux (~$49M), Allspice, Circuit Mind
In-browser design + chat copilot
Not us: Flux's "debug" is pasting a scope screenshot; not instrument-integrated
Code-as-source EDA
JITX, atopile, tscircuit, Diode
Define hardware in code
Not us: new design front-end; not the bench
Incumbents
Cadence, Siemens, Altium
AI folded into 30-yr suites
Not us: system design; not the cross-vendor bench
| Where money's going | Players | What they do | Why it's not us |
|---|---|---|---|
| Prompt-to-hardware (for beginners) | Schematik ($4.6M pre-seed, Lightspeed-led), Atech ($800K pre-seed, Sequoia · a16z · Lovable) | Plain-English idea → code, wiring, modules, first prototype | Built for people who "don't know what a resistor is." Idea to first prototype, not bring-up or debug of a real board. |
| Physics-driven layout | Quilter ($40M; real enterprise traction) | Autonomous PCB placement & routing | Pre-fabrication design. Explicitly not schematic gen, not bring-up. |
| Browser AI copilots | Flux (~$49M), Allspice, Circuit Mind | In-browser design + chat copilot | Flux's "debug" feature is pasting a scope screenshot into chat. It isn't instrument-integrated. |
| Code-as-source EDA | JITX, atopile, tscircuit, Diode | Define hardware in code | A new design front-end; doesn't touch the bench |
| Incumbents | Cadence (Allegro X AI), Siemens, Altium | AI folded into 30-yr-old suites | System-level design + simulation; not the cross-vendor bench |
The bring-up and debug wedge is wide open. A closed-loop, design-aware, cross-instrument agent is the one product none of them is building.
Defensibility: cross-vendor and design-aware from day one, plus a proprietary data flywheel: design intent paired with real measured outcomes nobody else collects.
"Won't the scope vendors (Keysight, R&S, Tektronix) just add their own AI?" They will. And it will be single-instrument and brand-locked, while real benches are mixed-vendor. The opening is exactly the place a Keysight copilot can't go: across all your instruments, tied to your design.
08 - Business model
Start as per-seat SaaS. Grow into the hardware the software runs on.
Today: software, priced against the labour we save
- • Per-seat subscription for each engineer at the bench. Land with the lead EE, expand across the hardware team.
- • We save a $150 to $300/hr engineer hours on every board they bring up. A four-figure seat is a rounding error against that.
- • Reference point: hardware-in-the-loop tools already sell at ~$5k/year to companies (per discovery).
- • Pure software, no hardware COGS, paid out of the labour budget, the largest and least-defended budget in the building.
The arc: software opens the market, hardware is the long-term moat
As AI drives the cost of software toward zero, code stops being defensible. The durable advantage is the bench itself: our own debug & capture hardware, designed around the agent. When every competitor can ship the software, the hardware is what drives adoption and retention.
- • The moat: a closed software-defined-instrument loop an incumbent scope vendor can't copy without rebuilding their software, and a SaaS competitor can't copy without building hardware.
09 - The ask
Raising a $500k pre-seed on a rolling SAFE to prove the wedge with paying design partners.
Target
$500k
Instrument
Rolling SAFE
single cap, uncapped tranches · cheques ≤ $250K
Stage
First investor conversations
investment window mid-July to mid-August
What it buys - 12 months to a priced seed
- 1 Ship the MVP that closes the schematic ↔ firmware ↔ instrument loop on real benches.
- 2 Get 3+ design partners paying. A cheque is the proof the pain is real and engagement is genuine.
- 3 Prove the wedge segment (funded robotics/aerospace teams).
- 4 Automate internal ops.
What I want from you, beyond the cheque
- • Intros to hardware teams (robotics, aerospace, consumer EE) for design partners.
- • Conviction that hardware is about to accelerate the way software did, and that coscope is the tooling layer for it.
Why $500k goes far: we're AI-native inside and out, compute over headcount. Tokens are the largest cost, not salaries, so this round behaves like a bigger one. And token costs keep falling fast, roughly 10× a year.