Assumption-driven venture validation and pitch workbench

For

Founders, venture teams and investment analysts validating business ideas before committing capital

Solves

Business ideas are pitched and funded on untested assumptions, scattered research and rehearsed answers that do not survive investor scrutiny.

Delivers

Reviewed assumption register linked to pitch materials

Built in

about 5 weeks of creation time, MVP in 6 days

Investment

$14,000 for the MVP, $47,500 for the full product

Run it

Inside your business, or as part of your offer to clients

Reduce wasted diligence cycles by testing critical assumptions before capital is committed.

1. Generate a structured business plan from a short brief.
2. Run repeatable validation workflows with named owners.
3. Support shared project workspaces and reviewer roles.
4. Connect to research, spreadsheet and publishing tools.
5. Track validation progress and report on outcomes.
6. Provide a low-learning-curve workspace for non-specialists.
7. Route support questions to a named operator.
8. Score the venture against documented investment strategy models.
9. Screen and rank comparable companies quantitatively.
10. Produce valuation, growth and indicator reports.
11. Track a portfolio and its holdings.
12. Send configurable alerts on signals and movements.
13. Identify critical assumptions that could change the outcome.
14. Publish ideas to collect real feedback and engagement metrics.
15. Analyse comments and reactions for sentiment.
16. Apply pitch structure templates.
17. Give AI-driven feedback on pitch content and delivery.
18. Simulate investor Q&A sessions.
19. Customise templates and feedback by industry and business model.

Everything these tools do, in one app

• Idea and content generation Generates written content or business plans from a brief description or prompt.Found in Impossibly Dope Innovations, Frederick AI
• Automated task workflows Automates repetitive tasks through customizable workflows.Found in Impossibly Dope Innovations
• Collaboration tools Enables teams to work together and manage projects.Found in Impossibly Dope Innovations
• Third-party integrations Connects with other software applications to enhance functionality.Found in Impossibly Dope Innovations
• Analytics and reporting Tracks progress and provides insights to optimize outputs.Found in Impossibly Dope Innovations, SharkTank AI
• Intuitive interface Provides a user-friendly interface that minimizes the learning curve.Found in Impossibly Dope Innovations, Validea, SharkTank AI
• Responsive customer support Offers timely support to address user questions.Found in Impossibly Dope Innovations
• Investment strategy models Evaluates stocks using multiple proven investment strategies based on well-known investors.Found in Validea
• Automated stock screening Screens and ranks stocks using quantitative analysis.Found in Validea
• Comprehensive stock reports Provides detailed reports including valuation, growth, and technical indicators.Found in Validea
• Portfolio tracking Monitors portfolio performance and tracks holdings.Found in Validea
• Customizable alerts Sends alerts for stock movements and strategy signals.Found in Validea
• Assumption analysis Identifies critical assumptions that could impact the success of a business idea.Found in Frederick AI
• Real-time validation Publishes ideas to social platforms to collect real user feedback and engagement metrics.Found in Frederick AI
• Sentiment analysis Analyzes comments and reactions to gauge public perception and interest.Found in Frederick AI
• Pitch structure templates Provides templates to organize pitch ideas effectively.Found in SharkTank AI
• AI-driven pitch feedback Offers feedback on pitch content and delivery to improve clarity and impact.Found in SharkTank AI
• Simulated Q&A sessions Simulates investor questions to help users prepare for real pitches.Found in SharkTank AI
• Customization for industries Allows customization of templates and feedback for different industries and business models.Found in SharkTank AI

What goes in, what comes out

The workflow

1. In
   Start with

   Written brief, market research, financial inputs and stakeholder feedback

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect a written brief

4. 3

   Market research

5. 4

   Financial inputs and stakeholder feedback

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Reviewed assumption register linked to pitch materials

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One defined venture stage and documented scoring model; final investment judgments and pitch claims remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Brief and assumption intake, Editable validation workspace, Review and pitch pack. Use a project gallery, a central canvas for assumptions, evidence and financial inputs, and a right-hand panel for sources, feedback and comments. Let users compare assumption versions side by side. Display draft, under review and validated states. Provide a reviewer link with comments anchored to the relevant assumption. Make the task-specific outcome reviewed assumption register linked to pitch materials visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, source versions, reviewer comments, approval states, usage allowances, revision limits, export history and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.

Integrations and data access

Founder-owned documents, authorized market research and permitted financial sources. Cloud storage, spreadsheet import/export and publishing destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

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. 1

   Scoping call

   Day 1

   Thirty 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. 2

   MVP

   6 days

   One buyer segment, one recurring use case; first modules: generate a structured business plan from a short brief; identify critical assumptions that could change the outcome. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   7 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   3 weeks

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We 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.

1. Pick the riskiest assumption. Here: will founders, venture teams and investment analysts validating business ideas before committing capital use it to solve "business ideas are pitched and funded on untested assumptions, scattered research and rehearsed answers that do not survive investor scrutiny"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Assumptions retired per diligence hour and pitch questions answered from evidence.
4. Measure, then decide. Track assumptions retired per diligence hour and pitch questions answered from evidence; 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: One defined venture stage and documented scoring model; final investment judgments and pitch claims remain human. Implement one approved input format, a bounded representative case set and the first two task modules: generate a structured business plan from a short brief; identify critical assumptions that could change the outcome. Support the remaining modules with operator review. 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 the reviewed assumption register linked to pitch materials. Retain the explicit scope boundary: One defined venture stage and documented scoring model; final investment judgments and pitch claims remain human.

What the build depends on. Document upload and preview, asynchronous generation jobs, editable version history, reviewer access and tested export formats. High-fidelity validation requires qualified financial and domain review. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One defined venture stage and documented scoring model; final investment judgments and pitch claims remain human.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

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.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test a USD 300-1,500 fixed pilot for one defined venture package. Offer a monthly validation allowance after repeat demand. Quote complex portfolio or multi-venture work separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewed assumption register linked to pitch materials. 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

Reduce wasted diligence cycles by testing critical assumptions before capital is committed. Demonstrate a concrete reviewed assumption register linked to pitch materials using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Founders, venture teams and investment analysts professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample assumption register linked to pitch materials from a small authorized input set, with a transparent calculation of assumptions retired per diligence hour and pitch questions answered from evidence and no promised savings.

The first 30 days

1. Week 1: interview five founders, venture teams and investment analysts validating business ideas before committing capital and inspect a recent example of business ideas pitched and funded on untested assumptions, scattered research and rehearsed answers that do not survive investor scrutiny.
2. Week 2: prepare a consented or synthetic demonstration of the three task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure assumptions retired per diligence hour and pitch questions answered from evidence, 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: Assumptions retired per diligence hour and pitch questions answered from evidence. 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

Assumptions retired per diligence hour and pitch questions answered from evidence; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs a reviewed assumption register linked to pitch materials. 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 reusable library of approved scoring models, validation cases and reviewer corrections, together with reliable delivery for a narrow venture niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for founders, venture teams and investment analysts validating business ideas before committing capital. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Impossibly Dope Innovations, Validea, Frederick AI and SharkTank AI, plus spreadsheets, consultants and generic writing tools. Compare this product with the buyer's present method on assumptions retired per diligence hour and pitch questions answered from evidence. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Generation attempts, research and data processing, storage, reviewer hours, client revision rounds and licensed source material. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of the reviewed assumption register linked to pitch materials. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve source attribution, financial accuracy and usage permissions. Named reviewers approve substantive assumptions and pitch claims. One defined venture stage and documented scoring model; final investment judgments and pitch claims remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.