Gatien
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Gatien
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Budget
The cost of an AI prototype depends less on the word “AI” than on the workflow you want to test. A simple extraction on a few examples is not the same effort as an assistant connected to several sources, with permissions, logs, an interface, and quality tests. This page helps you estimate the factors before asking for a quote.
What can be built
Every project starts from a real workflow, real examples, and an output the team can check.
Volume, format, quality, confidentiality, and available examples change the effort a lot.
An isolated demo is simpler than a workflow connected to a CRM, ERP, inbox, or internal tool.
The more reliable, traceable, and tested the output must be, the more you invest in guardrails.
A tool for one person in a test does not have the same requirements as usage by a whole team.
Use cases
These examples are a starting point. The right scope depends on your data, your users, and the business risk.
Test an idea with a few examples and a simple interface.
Connect AI to an existing workflow to measure the real gain.
Handle confidential data, permissions, logs, and reviews.
Prepare a feature meant to enter an existing application.
How a mission runs
Clarify the business problem, the users, the available data, the constraints, and the expected result.
Build a first testable version on real examples, without overbuilding the architecture.
Check answers, errors, edge cases, permissions, and how much human review is needed.
Connect the tool to existing systems: internal app, CRM, Slack, Teams, email, document store, or API.
Hand over a maintainable base: code, configuration, known limits, success criteria, and next steps.
Stack
Deliverables
Scope
FAQ
Want to estimate an AI prototype? Send the workflow, the available data, and the level of integration you want.
Contact GatienBecause two AI prototypes can have very different levels of integration, security, and quality.
Reduce the scope, provide clean examples, avoid unnecessary integrations at the start, and define a verifiable output.
Ask for the scope, required data, integrations, success criteria, documentation, and known limits.
Read next
A first useful version that turns a hunch into a product or operations decision.
A page so you know what to expect before handing over an AI project.
A decision guide for choosing the right format based on risk, budget, speed, and technical need.