Meeting-to-experiment execution studio
Convert discussion into measurable operational learning.
- For
- Continuous improvement teams
- Solves
- Retrospectives generate ideas that never become bounded trials.
- Delivers
- Reviewed improvement experiment workspace
- Built in
- about 4 weeks of creation time, MVP in 4 days
- Investment
- $19,000 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
Convert discussion into measurable operational learning.
- Turn proposals into test charters.
- Assign accepted owners.
- Compare observed results against gates.
- Compare the reviewed result with the recorded baseline and value assumptions.
- Capture corrections and named-owner approval before consequential use.
- Export a versioned reviewed improvement experiment workspace with source references and unresolved questions.
What goes in, what comes out
- Team-approved improvement proposals
- Measurement constraints
AI drafts, people review. Operational coordination portal.
- Reviewed improvement experiment workspace
How it works
The workflow
- InStart with
Team-approved improvement proposals and measurement constraints
- 1
Confirm the buyer's problem and scope
- 2
Collect team-approved improvement proposals and measurement constraints
- 3
Then follow this sequence: 1
- OutFinish with
Reviewed improvement experiment workspace
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. No automatic policy changes; teams approve each trial. A model suggestion is never a verified fact, professional decision or authorization to act.
What your team sees
Primary screens: Request and prerequisites, Owner-controlled task board, Completion evidence. Use a queue or timeline as the opening view, with clear owners, dates and current states. Each case opens into its source context, proposed actions and discussion. Give external participants a limited form or status page. Make the next required action visible without opening every record. Make the task-specific outcome reviewed improvement experiment workspace visible beside its evidence, review state and value baseline.
Accounts and administration
Role permissions, task ownership, deadlines, reminders, approval gates, exception handling, action history, duplicate prevention and reversible configuration. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.
Integrations and data access
Team updates, calendars, project records and agreed management routines. Calendars, email, task managers and relevant business records. Use draft actions and supervised handoffs first, then enable only specifically authorized writes. 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: turn proposals into test charters; assign accepted owners. 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 continuous improvement teams use it to solve "retrospectives generate ideas that never become bounded trials"?
- 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: Validated improvements realized minus experiment and coordination costs.
- Measure, then decide. Track validated improvements realized minus experiment and coordination costs; 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: No automatic policy changes; teams approve each trial. Implement one approved input format, a bounded representative case set and the first two task modules: turn proposals into test charters; assign accepted owners. Support the third module with operator review: compare observed results against gates. 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 reviewed improvement experiment workspace. Retain the explicit scope boundary: No automatic policy changes; teams approve each trial.
What the build depends on. Explicit state definitions, owner mapping, approval rules, idempotent actions, notifications and recovery procedures. Workflow reliability matters more than fluent text. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: No automatic policy changes; teams approve each trial.
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: turn proposals into test charters; assign accepted owners. 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 $19,000
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
Continuous improvement teams run it inside the business: team-approved improvement proposals and measurement constraints in, reviewed improvement experiment workspace 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
#272e91 - accent
#c9bf54 - surface
#e4e5f1 - ink
#22201e
- Headings
- Fraunces
- Text
- Inter
- Voice
- Practical, organised, candid
Selling it to your own clients: the go-to-market playbook
Pricing to test
Test USD 750-2,500 setup plus USD 200-800 monthly for one bounded workflow and team. Cap case volume and implementation scope. Larger operational integrations need separate quotes. Prices are hypotheses. Package the initial sale as one bounded reviewed improvement experiment workspace. 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
Convert discussion into measurable operational learning. Demonstrate a concrete reviewed improvement experiment workspace using the buyer's approved example and show the baseline, corrections and actual delivery effort.
Where to find buyers
Continuous improvement teams professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.
Lead magnet
A reviewed sample reviewed improvement experiment workspace from a small authorized input set, with a transparent calculation of validated improvements realized minus experiment and coordination costs and no promised savings.
The first 30 days
- Week 1: interview five continuous improvement teams and inspect a recent example of retrospectives generate ideas that never become bounded trials.
- 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 validated improvements realized minus experiment and coordination costs, 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: Validated improvements realized minus experiment and coordination costs. 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
Validated improvements realized minus experiment and coordination costs; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.
Retention and expansion
Repeat the workflow when the buyer again needs reviewed improvement experiment workspace. 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
Customer-specific workflow rules, reliable handoffs, operational history and integrations that make the service part of daily work. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for continuous improvement teams. Repeatable delivery and useful integrations matter more than access to a base model.
Alternatives and positioning
Shared inboxes, spreadsheets, task boards and existing workflow automation products. Compare this product with the buyer's present method on validated improvements realized minus experiment and coordination costs. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.
Main delivery costs
Workflow configuration, integration maintenance, model calls, notification delivery, exception support and monitoring. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of reviewed improvement experiment workspace. Track cost per accepted output, including correction work, unsuccessful cases and support.
Safeguards
Confirm owners, decisions and commitments. Keep employee discussion notes access-controlled and avoid covert individual performance inference. No automatic policy changes; teams approve each trial. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.