The full answer
Data readiness is often the biggest variable. If your documents and records are already organised and accessible, a project moves quickly. If data is scattered, inconsistent or locked in legacy systems, some of the work goes into preparing it before the AI can use it.
Integration effort matters too. A standalone assistant is simpler than an agent that reads and writes across a CRM, ERP and support platform, each with its own permissions and edge cases.
Accuracy requirements change the amount of evaluation, testing and human review needed. A drafting tool where a person checks every output needs less safeguarding than a system making decisions with financial or medical consequences.
AI products also have running costs that traditional software does not: model usage charged per request or per token, vector database hosting and, for self-hosted models, GPU infrastructure. Creuto estimates these during discovery and designs to keep them predictable, for example by routing simple requests to smaller models.
Creuto does not publish prices because these factors vary widely. The proposal sets out a budget breakdown, milestones and timeline for your specific project.