
Physical prototype test pooling network
Make useful prototype testing affordable through shared capacity.
- For
- Independent hardware makers
- Solves
- Small teams cannot afford specialist test capacity individually.
- Delivers
- Engineer-approved testing placement
- Built in
- about 4 weeks of creation time, MVP in 4 days
- Investment
- $24,000 for the MVP, $50,000 for the full product
- Run it
- Inside your business, or as part of your offer to clients
What it does
Make useful prototype testing affordable through shared capacity.
- Bundle compatible nonconfidential requests.
- Match qualified facilities.
- Prepare reviewed test briefs.
- Compare the reviewed result with the recorded baseline and value assumptions.
- Capture corrections and named-owner approval before consequential use.
- Export a versioned engineer-approved testing placement with source references and unresolved questions.
What goes in, what comes out
- Engineer-approved test needs
- Lab-declared availability
AI drafts, people review. Transparent opportunity matching and shortlist platform.
- Engineer-approved testing placement
How it works
The workflow
- InStart with
Engineer-approved test needs and lab-declared availability
- 1
Confirm the buyer's problem and scope
- 2
Collect engineer-approved test needs and lab-declared availability
- 3
Then follow this sequence: 1
- OutFinish with
Engineer-approved testing placement
AI does the heavy lifting, people stay in charge
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Labs determine suitability and safety; confidential designs stay isolated. A model suggestion is never a verified fact, professional decision or authorization to act.
What your team sees
Primary screens: Verified offer or need profiles, Explainable match comparison, Mutual approval and handoff. Open with a filterable opportunity feed and clear fit explanations. Each profile shows source evidence, eligibility conditions and missing information. Keep saved, rejected and needs-review states. Include a deadline or next-action view without hiding the basis of recommendations. Make the task-specific outcome engineer-approved testing placement visible beside its evidence, review state and value baseline.
Accounts and administration
Editable criteria, dated sources, eligibility evidence, missing-data flags, saved shortlists, rejection reasons, deadline alerts and owner follow-up. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.
Integrations and data access
Product feedback, authorized interviews, usage exports and requirement records. Permitted opportunity feeds, customer profiles, calendars and CRM exports. Keep initial outreach or applications as user-reviewed drafts. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
How we build it
We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.
- 1
Scoping call
Day 1Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.
- 2
MVP
4 daysOne buyer segment, one recurring use case; first modules: bundle compatible nonconfidential requests; match qualified facilities. Manual review in the loop. Built by our AI software factory.
- 3
Paid pilot
5 daysAccounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- 4
Full product
9 daysSelf-serve onboarding, billing, monitoring and the wider integration set.
- 5
Run and improve
MonthlyWe host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.
Why we start with an MVP
An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.
- Pick the riskiest assumption. Here: will independent hardware makers use it to solve "small teams cannot afford specialist test capacity individually"?
- Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
- Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Accepted test evidence per total testing and logistics cost.
- Measure, then decide. Track accepted test evidence per total testing and logistics cost; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.
MVP scope for this solution. Pilot scope: Labs determine suitability and safety; confidential designs stay isolated. Implement one approved input format, a bounded representative case set and the first two task modules: bundle compatible nonconfidential requests; match qualified facilities. Support the third module with operator review: prepare reviewed test briefs. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around engineer-approved testing placement. Retain the explicit scope boundary: Labs determine suitability and safety; confidential designs stay isolated.
What the build depends on. Current source information, explicit eligibility rules, entity identity checks and inspectable fit reasoning. Sparse evidence limits match quality. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: Labs determine suitability and safety; confidential designs stay isolated.
Investment
A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.
- Phase 1
MVP
One buyer segment, one recurring use case; first modules: bundle compatible nonconfidential requests; match qualified facilities. Manual review in the loop.
- Phase 2
Paid pilot
Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- Phase 3
Full product
Self-serve onboarding, billing, monitoring and the wider integration set.
Indicative total, MVP to full product$50,000about 4 weeks of creation time · start with the MVP from $24,000
Running costs per month
A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.
| Stage | Hosting and infrastructure | AI usage | Total per month |
|---|---|---|---|
| MVP and paid pilotabout 3 customers | $30–$60 | $40–$90 | $70–$150 |
| Full productabout 50 customers | $110–$210 | $280–$560 | $390–$770 |
Run it or resell it
For your own team
Independent hardware makers run it inside the business: engineer-approved test needs and lab-declared availability in, engineer-approved testing placement out, reviewed by your people.
As part of your offer
Agencies, consultancies and software companies can offer it to their own clients under their brand. We build and maintain it; you sell and deliver it.
Your brand, or this one
Run it under your own brand, or start from this concept style.
- primary
#6f2791 - accent
#7bc954 - surface
#ede4f1 - ink
#22201e
- Headings
- Fraunces
- Text
- Inter
- Voice
- Curious, rigorous, user-led
Selling it to your own clients: the go-to-market playbook
Pricing to test
Test USD 150-600 monthly for one narrow opportunity feed, or USD 750-2,500 for a bespoke researched shortlist. Price manual verification and custom research explicitly. These are pricing hypotheses. Package the initial sale as one bounded engineer-approved testing placement. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.
Message to test
Make useful prototype testing affordable through shared capacity. Demonstrate a concrete engineer-approved testing placement using the buyer's approved example and show the baseline, corrections and actual delivery effort.
Where to find buyers
Independent hardware makers professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.
Lead magnet
A reviewed sample engineer-approved testing placement from a small authorized input set, with a transparent calculation of accepted test evidence per total testing and logistics cost and no promised savings.
The first 30 days
- Week 1: interview five independent hardware makers and inspect a recent example of small teams cannot afford specialist test capacity individually.
- Week 2: prepare a consented or synthetic demonstration of the three task modules.
- Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
- Week 4: measure accepted test evidence per total testing and logistics cost, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.
Paid pilot
Agree quality and outcome thresholds before the pilot using this measure: Accepted test evidence per total testing and logistics cost. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.
Success metrics
Accepted test evidence per total testing and logistics cost; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.
Retention and expansion
Repeat the workflow when the buyer again needs engineer-approved testing placement. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.
Why clients would pick it
A maintained niche opportunity dataset and documented relevance feedback, supported by relationships with the intended buyer community. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for independent hardware makers. Repeatable delivery and useful integrations matter more than access to a base model.
Alternatives and positioning
Manual research, directories, generic databases, referrals and existing opportunity marketplaces. Compare this product with the buyer's present method on accepted test evidence per total testing and logistics cost. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.
Main delivery costs
Source collection, profile updates, entity resolution, eligibility verification, analyst research and customer feedback review. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of engineer-approved testing placement. Track cost per accepted output, including correction work, unsuccessful cases and support.
Safeguards
Use consented research and preserve contradictory evidence. Separate observed user behavior, proposed explanations and untested product assumptions. Labs determine suitability and safety; confidential designs stay isolated. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.