Short Answer
AI Prototype engagements for startup teams commonly fall around $25,000-$90,000 depending on data, model workflow, evaluation, and integrations, but the final budget should be scoped after reviewing workflow complexity, integrations, security, design assets, and launch goals.
Primary Cost Drivers
The biggest cost drivers are user roles, core workflows, data model complexity, third-party integrations, AI scope, mobile requirements, cloud infrastructure, QA, admin tooling, and post-launch support.
A smaller release is not automatically worse. A narrower launch can be better if it proves the product assumption faster and avoids building features that no user has validated.
| Tier | Includes | Typical use |
|---|---|---|
| Lean | Discovery, prototype, one core workflow | Investor or pilot validation |
| Standard | Production app, auth, admin, analytics | First customer release |
| Advanced | Multiple roles, integrations, AI, reporting | Complex pilot or scale-up |
Timeline Drivers
Discovery usually takes 1-2 weeks. Prototypes often take 2-4 weeks. Production builds commonly take 6-16 weeks depending on scope.
Timelines stretch when requirements are unclear, third-party access is delayed, regulated data is involved, or the product needs both web and mobile surfaces.
Helpful References
Authority sources
FAQ
How much does AI prototype cost?
AI Prototype commonly falls around $25,000-$90,000 depending on data, model workflow, evaluation, and integrations, but exact pricing depends on scope, integrations, design readiness, platforms, security, and launch support.
How long does AI prototype take?
A focused prototype can take 2 to 4 weeks. A production build commonly takes 6 to 16 weeks depending on complexity and dependencies.
Can Kraydl provide a fixed estimate?
Kraydl can provide a scoped estimate after reviewing workflow, features, integrations, design assets, technical constraints, and launch goals.
What makes the budget increase?
Complex integrations, multiple user roles, sensitive data, mobile platforms, AI workflows, custom reporting, and advanced admin tools usually increase cost.
What can reduce cost?
Clear scope, existing designs, a narrow first workflow, fewer integrations, and realistic launch criteria can reduce cost and timeline.
Build the right version first.
Bring Kraydl the workflow, launch goal, risk constraints, and timeline. We will help turn it into a scoped product plan and a build path founders can actually use.