A practical model that covers the current process, implementation, ongoing operation, human review, and the cost of errors
Measure transaction volume, handling time, labor cost, error and rework rates, lost revenue, and any SLA penalties. Without a baseline, improvement cannot be demonstrated
Time saved, fewer errors, greater throughput, faster revenue, and lower risk must be calculated separately. Do not count the same freed capacity twice
Total cost of ownership includes audit, development, integrations, AI model usage, infrastructure, monitoring, human review, support, and future changes
Before development, define the minimum effect, maximum cost per operation, acceptable manual review rate, and unacceptable error classes
You do not need a detailed brief to begin
If the baseline is unclear, start with an AI opportunity audit; for the full delivery path, see AI implementation in Belarus
Learn how we assess the process, business case, data security, and quality before development begins
Explore the methodology →Determine whether the task calls for AI, rule-based automation, or a process redesign
Assess a process →Send the current process, constraints, and expected outcome, and we will suggest a practical first step
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