AI Proof Sprint
Turn one AI use case into tested proof in 10 business days.
The AI Proof Sprint gives you a controlled working prototype, measurable acceptance criteria, and a defensible production decision — for a fixed $5,000. CodyHire reviews the available data, models, integrations, and constraints, then builds and evaluates one bounded workflow.
Price: $5,000 fixed · Signing: $2,500 (50%) · Final: $2,500 (50%) before handoff
Duration:10 business days after inputs and access are available · Scope: One bounded AI workflow, product interaction, or agent behavior
This is a controlled prototype engagement, not a production application, live pilot, or managed service. Production deployment, enterprise security, formal compliance, and service-level guarantees are not included.
A fixed-scope engagement with a clear decision at the end.
- Price
- $5,000 fixed
- Signing
- $2,500 (50%)
- Final
- $2,500 (50%) before handoff
- Duration
- 10 business days after required inputs and access are available
- Scope
- One bounded use case — not several unrelated ideas
- Output
- Controlled working prototype, acceptance cases, findings, recommendation, production roadmap, and estimate
- IP
- Client owns engagement-specific deliverables after final payment
- NDA
- Available before sensitive disclosure
Build, revise, or stop — based on evidence, not assumptions.
The Sprint turns an abstract use case into an observable test. The purpose is to determine technical feasibility, identify critical constraints, and understand what a production build would still require. It does not guarantee that the original idea will prove viable — and that finding is itself a valuable outcome.
- 1
Can the proposed AI behavior work with the available data, models, APIs, or systems?
- 2
Which part of the use case carries the most technical or operational risk?
- 3
What is the smallest useful production scope if the proof supports proceeding?
- 4
What security, privacy, reliability, integration, or monitoring requirements remain?
- 5
What should the next phase include, change, or avoid?
Nine deliverables that turn uncertainty into a decision.
- 01
Use-case and decision definition
Document the intended user, the action or decision AI should support, and the question the Sprint must answer.
- 02
Feasibility review
Assess the available data, models or APIs, integrations, privacy constraints, and operating risks that affect the use case.
- 03
Agreed proof scope
Select one narrow workflow or interaction that can answer the central question.
- 04
Controlled working prototype
Build the agreed core behavior in a sandbox or controlled environment. The prototype supports observation and evaluation, not production use.
- 05
Acceptance cases and observed limitations
Document what worked, what did not, and what remains uncertain.
- 06
Integration, reliability, security, and operational findings
Record the requirements, blockers, and risks identified during the Sprint.
- 07
Go, revise, or stop recommendation
A clear assessment of whether the evidence supports proceeding, changing direction, or stopping.
- 08
Production architecture direction, phased roadmap, and estimate
The architecture direction, missing production requirements, phased scope, and an estimate for the next build decision.
- 09
Final demonstration and handoff
Present the working prototype and deliver engagement artifacts after final payment.
Five focused phases from question to evidence.
- 01
Define the decision and use case
Align on the intended user, current problem, proposed AI-supported action, and the question the prototype must answer.
- 02
Review feasibility and agree scope
Assess data, models, integrations, privacy, reliability, and operating conditions. Choose the narrowest interaction that can answer the central question.
- 03
Build the controlled prototype
Implement the agreed core behavior in a sandbox or controlled environment using the inputs and access available for the Sprint.
- 04
Demonstrate, observe, and evaluate
Review the working behavior against the agreed question. Capture useful outputs, failure modes, feedback, and unresolved risks.
- 05
Hand off deliverables and production roadmap
Deliver the engagement artifacts. Document architecture direction, missing production requirements, phased scope, known risks, and the estimate for a possible next phase.
Process note: All five phases fit within the 10-business-day Sprint. The client must provide timely access, context, feedback, and a decision-maker during that window.
Clear boundaries protect the value of the proof.
The Sprint proves one behavior. Work outside this scope receives a separate estimate rather than silently extending the timeline or reducing quality.
Not included
- A complete production application or live pilot
- Production availability, SLA, or ongoing operation
- Formal compliance or certification
- Unlimited revisions or multiple unrelated use cases
- Major data cleaning, model training, or legacy-integration programs
- Guaranteed feasibility, accuracy, adoption, funding, revenue, savings, or ROI
A successful Sprint starts with clear inputs.
Required inputs
- One bounded use case with a specific intended user
- One action or decision AI should support
- Relevant sample data, content, API access, or system access
- Known privacy, reliability, integration, or operational constraints
- A clear question the proof must answer and acceptance criteria that can be observed
- A decision and payment owner available for timely feedback during the Sprint
- Budget readiness for the $2,500 deposit and final $2,500 before handoff
Clear commercial terms from the start.
- Price
- The AI Proof Sprint is $5,000 fixed — $2,500 at signing and $2,500 before final handoff.
- IP ownership
- The client owns engagement-specific deliverables under the signed agreement after final payment.
- NDA
- An NDA is available before sensitive disclosure. The signed document controls its exact terms.
- Scope changes
- Work outside the agreed use case or deliverables receives a separate estimate.
When the evidence is strong, the same team can build the production system.
If the Proof Sprint supports proceeding, the separately scoped AI Production Build can implement the validated workflow as a live system — with integrations, controls, deployment, documentation, and handoff. The production engagement starts at $15,000.
This is not an automatic upsell. The Sprint may recommend revising the scope or stopping entirely. That is a successful outcome.
U.S.-based team with a delivered production launch.
Modern Mechanic
Owner confirmedFrequently asked questions.
What can I test in the AI Proof Sprint?
The Sprint can test one bounded AI workflow, product interaction, or agent behavior. The use case must have an intended user, available inputs, and a specific action or decision to evaluate. Multiple unrelated ideas require separate scopes.
What if the use case does not prove feasible?
The Sprint does not guarantee that the original idea will work. A useful outcome may be evidence that the scope, data, architecture, or direction needs to change — or that the team should not fund the proposed build yet. Those findings belong in the roadmap.
Will I receive code and artifacts?
Yes. The handoff includes the prototype artifacts and code created for the engagement. The client owns the engagement-specific deliverables under the signed agreement after final payment.
Is an NDA available?
Yes. An NDA is available before sensitive disclosure. The signed document controls its exact terms and obligations.
How is the $5,000 paid?
$2,500 (50%) is due at signing. The remaining $2,500 (50%) is due before final handoff.
Can CodyHire build the production system after the Sprint?
If the proof supports proceeding, the separately scoped AI Production Build can implement the validated workflow. The Sprint and Production Build are separate engagements with separate scopes and agreements.
Does the Sprint guarantee ROI, accuracy, or adoption?
No. The Sprint is designed to test technical behavior and support a better-informed build decision. It does not guarantee market fit, user adoption, funding, revenue, cost savings, or ROI.
Next decision
Have one AI use case worth proving first?
Book a 20-minute fit call to confirm the intended user, proof question, available inputs, budget, and timing.