AI Initiative Value Underwriter
AI Initiative Value Underwriter
Turn scattered AI pilot data into a traceable, reproducible business case that your team can actually review and challenge.
What problem does it solve?
Many AI initiatives begin with promising benefit estimates but lack a reliable baseline, complete cost structure, traceable evidence, or clear decision criteria. This makes ROI difficult to verify and leaves teams uncertain about whether to fund, scale, pause, or stop a project.
AI Initiative Value Underwriter helps you structure your operating data, costs, pilot results, assumptions, and evidence into a decision-ready value assessment.
What it does
- Validates required business, cost, benefit, and evidence inputs
- Keeps missing information visible instead of inventing benchmarks
- Calculates Total Cost of Ownership (TCO)
- Calculates Return on Investment (ROI)
- Calculates Net Present Value (NPV)
- Estimates the payback period
- Separates one-time, recurring, and usage-based costs
- Builds downside, base, and upside scenarios
- Identifies weak evidence and possible benefit double-counting
- Flags missing owners, dates, assumptions, and governance gates
- Produces machine-readable JSON and a readable Markdown decision memo
- Recommends the next evidence or decision step
Who is it for?
- AI agencies preparing or reviewing client proposals
- Enterprise AI and transformation leaders
- Product, operations, and business owners
- Finance partners and internal review teams
- Teams deciding whether an AI pilot should be funded or scaled
Common use cases
- Build an AI initiative value case before requesting funding.
- Decide whether to scale, hold, redesign, or stop an AI pilot.
- Test whether a claimed cost saving has a valid baseline and owner.
- Compare build, buy, and workflow-redesign scenarios.
- Prepare a structured decision memo for internal review.
What you provide
You provide aggregated project information such as:
- Decision horizon and thresholds
- Annual transaction or workload volume
- Current processing time and error rate
- Loaded labor cost
- Expected time or quality improvement
- Benefit realization assumptions
- One-time implementation costs
- Recalling operating, model, and maintenance costs
- Usage-based costs
- Benefit ramp assumptions
- Evidence sources, dates, owners, and confidence levels
If critical information is missing, the Agent returns NOT_READY with a prioritized evidence plan instead of fabricating an answer.
What you receive
- A validated intake assessment
- Calculation JSON with formula traceability
- TCO, ROI, NPV, and payback results
- Cost and benefit breakdowns
- Downside, base, and upside scenarios
- Evidence coverage and confidence limits
- Counterevidence, unknowns, and risk gates
- A Markdown decision memo
- Recommended conditions and next actions
Why not use a general-purpose AI model?
General AI models can write persuasive business cases, but they may hide missing baselines, mix facts with assumptions, double-count benefits, or produce inconsistent calculations across conversations.
This Agent combines a fixed evidence method with deterministic calculations, explicit sensitivity analysis, counterevidence checks, and confidence limits.
Data and privacy
User-provided JSON is processed through local sandbox validation and calculation. The included scripts do not make external network requests, use developer-controlled third-party services, or create a persistent database.
Use aggregated business values and role names whenever possible. Do not submit passwords, API keys, bank details, customer records, employee names, health information, government identifiers, or unnecessary confidential documents.
Platform-level model and sandbox processing remain subject to Capafy’s current policies.
Important limitations
- Results are only as reliable as the inputs and evidence provided.
- No live market data, external benchmarking, or currency conversion is included.
- All monetary inputs must use the same declared currency.
- The Agent does not automatically connect to internal business systems.
- A favorable scenario is not an approval or a guarantee of results.
- Outputs are project scenario analyses, not investment, accounting, audit, tax, legal, medical, or compliance advice.
- Final decisions must be made by accountable human owners.
Frequently asked questions
Does it connect to my systems?
No. You provide structured inputs, and no system credentials are required.
Does it guarantee ROI?
No. It models the scenarios you provide and makes uncertainty visible.
What happens when information is missing?
It returns NOT_READY with a prioritized evidence plan.
Can it approve an AI project?
No. It supports analysis and preparation; accountable people make the decision.
Does it require an external API or third-party account?
No. The included scripts require no API key or external service.
What is the difference between the free and paid versions?
The free Readiness Check identifies whether your evidence is complete enough for analysis. The Value Underwriter adds TCO, ROI, NPV, payback, sensitivity scenarios, risk gates, and a complete decision memo.
