The cost of an AI implementation: pilot and operating budget
AI implementation cost is driven by workflow complexity, data quality, integrations and the consequence of error more than by the model brand.
Current studio reference points
Our listed starting points are ₽60,000 for a scripted bot, ₽150,000 for a knowledge-grounded AI adviser, ₽300,000 for an assistant that uses external systems and ₽600,000 for coordinated assistants.
Separate discovery, integration, evaluation, infrastructure and support because each grows for different reasons and has a different owner.
Separate build and operation
Discovery, data preparation, integration, evaluation and documentation are project costs. Model calls, infrastructure, storage, monitoring and quality review continue after launch.
Inference cost depends on model, input size, output length and concurrency; measure an actual workload instead of multiplying a demo request.
Why production costs more than a demo
A production service must apply current permissions, survive CRM downtime, prevent duplicate actions, expose failures and control spend. These contracts—not the prompt—usually dominate engineering work.
Include preparation of documents and reference answers, as poor source material transfers cost into repeated manual correction after launch.
Limit budget risk
Start with one fixed workflow, define a pilot pass condition, cap usage, prove recommendations before automatic actions and require data export plus operating documentation.
A pilot budget should buy a decision: defined thresholds, observed operating cost and evidence for stopping, redesigning or expanding.
Need an estimate for your project?
Tell us about the project. We will break it into stages and explain the budget drivers.