Opportunities › Firmware simulation and testing for AI-assisted development › Proposed app
Tickrun
Cycle-accurate firmware simulation your CI and AI agents can call in seconds
- Score
- 28
- confidence 52
- Evidence
- 9
- items on the page
- Rivals
- 2
- named in sources
- First version
- 90 d
- estimate
- Type
- Desktop app
- PWA: runs in the browser, installs on Mac and Windows
- Market since
- 2003
- Mature market · AI estimate
ScreensConcept
Desktop app: Firmware engineers analyze timing traces and test results through APIs and CI steps during intensive development and code review work. Sample screens on a computer, in the proposed brand. Their numbers are sample data.
Run #482
1 scenario failedPASS 14/15
- Branch
About this appAI proposal
Tickrun runs your compiled firmware against a simulated microcontroller and returns pass or fail with a timing trace, through an API, a CLI or a CI step. No board to flash, no bench to book. An AI agent can change code, run the test and read the result in seconds.
Built for firmware teams on bare-metal and RTOS projects, such as flight controllers, robotics, satellites and electric vehicles. You write scenarios: inputs on pins and buses, injected faults, and timing limits. Tickrun checks each one on every commit.
The material reports that open-source emulators are slow and not accurate enough on timing. Tickrun is narrower: it models fewer chips and peripherals, and it tracks timing. Each run produces evidence a reviewer, human or AI, can read.
- Tagline
- Test the firmware before the board arrives.
- Voice
- PrecisePlainCalm
- Why this name
- A tick is one clock step, the unit firmware timing is measured in. Run is what you do on every commit. Two plain words.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
Run firmware through an API
Send an ELF and a scenario, get a verdict, logs and a timing trace back. Agents can call it directly with no human flashing a board.
No member yet
Timing assertions
Set limits on interrupt latency, loop period and deadline misses. A run fails when the firmware breaks a limit, with the cycle where it happened.
No member yet
Fault injection
Drop a sensor, corrupt a bus frame, brown out the supply or stall a clock in a scenario file, then see how the firmware recovers.
No member yet
CI step on every commit
A GitHub Actions step and a CLI run your scenario suite on each push. Results appear on the pull request.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#14222BDeep Slate · primary#F4F1EAPaper · surface#1B1F23Ink · text#E8A23ASignal Amber · accent#2F8F6BTrace Green · pass data#C0453AFault Red · fail data
Typography
Aa
Tickrun
PricingAI proposal
The material gives no competitor prices; QEMU and Renode are open source. These tiers are a starting point to test, set against hardware modules the material says cost over $100k.
Local
Free
- Local CLI for one chip family
- Unlimited local runs
- Community support
Team
$199 a month
- Cloud API and CI step
- 5 chip profiles
- 2,000 cloud runs a month
- Run links and review notes
Scale
$899 a month
- All chip profiles
- 20,000 cloud runs a month
- Private runners
- Priority support
What it could be worthEstimate
What a software business making this much sells for today, from real deals. Pick a monthly revenue.
If it makes
Worth about
$190,000
Sale range $132,000 to $263,000
$120,000 a year in revenue
From 87 software businesses listed and sold on Empire Flippers in the last year, revenue vetted by the broker: they sell for about 19× their monthly revenue, most between 13× and 26×.
Measured on profit, the middle deal is 32× monthly net profit: about 2.7 years of profit.
An estimate, not an offer or financial advice. A real price depends on profit, growth, churn, how much of the work is the owner's, and the buyer.
How it would growAI proposal
How the product would reach new customers through its own use, and how the first ones would be found. A plan to test, not a result.
- Built-in loop
- Partners and integrations. Tickrun runs as a GitHub Action and CLI. Results appear on pull requests, where teammates see them, and AI coding agents can call the API as a tool.
- Do they become customers?
- Teammates who see results on pull requests may become users, but exposure is not purchase. Test whether engineers who see PR results start their own team trial.
- First customers
- Embedded teams of 5 to 30 engineers building drone or robotics flight and motion control on one Cortex-M family, with a CI pipeline already in place.
- Where to reach them
- Hacker News and embedded forums: Share a worked example: a timing bug found in seconds by simulation, with a replayable run link.
- Drone and robotics communities: Offer free chip profiles to open-source flight controller projects in return for public case studies.
- Direct outreach: Contact firmware leads at space and robotics startups that wait on costly dev modules.
- First milestone
- Five teams on one chip family run Tickrun in CI for 30 days, and at least two agree to pay.
Why people already pay for this
- VerifiedHacker News post received 23 points and 10 comments
- Public claimFirmware engineers must manually flash physical boards and run tests with old tools, a process that takes hours and blocks AI agents from autonomous testing.
- Public claimSafety-critical firmware development (avionics, automotive) is blocked by hardware costs and testing friction, with individual hardware modules costing over $100k.
- Public claimA satellite startup needed to test firmware on hardware not yet owned; development modules cost over $100k, solved at a hundredth of the cost and time with simulation.
Tech stack
Every proposal builds on the same PWA base, installable from the browser on any phone or computer. Dashed boxes are what this app adds.
- AppNext.js and TypeScript
- PWAManifest and service worker
- UITailwind CSS
- Data and authSupabase Postgres
- PaymentsStripe
- EmailResend
- HostingVercel
- This app · Simulation engineNative core in Rust, compiled to CLI and serviceTiming-accurate, fast runs need compiled code, not a web runtime.
- This app · Run workersSandboxed containers on autoscaling workersCustomer firmware runs in isolation and bursts with CI traffic.
RisksAI inference
- TechnicalMatching real silicon timing is hard. If results differ from hardware on one chip, trust is lost. Start with one chip family and validate against a real board.
- CommercialSafety-critical teams may still require hardware tests for certification, so simulation may be seen as an add-on, not a replacement.
- DataAccurate peripheral models depend on vendor documentation, which may be incomplete or restricted.
- AIAI-written review notes may overstate what the simulation proves. Notes must list only measured results and what was not covered.
- CommercialFree open-source tools exist, so buyers must see a clear speed and timing gain to pay.
Everything marked AI proposal or AI inference was written by a model from the evidence on the opportunity page. The proposed name must be checked against trademark registers before it is used.