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.
Discuss your project →