Hand repetitive workflows to an AI agent that decides and self-heals
We build AI agents that read documents, call tools, make decisions and self-heal on failure — for testing, support, data processing and review workflows. Every step from assessment to POC to delivery is traceable.
Map existing workflows, system interfaces and data boundaries; define the agent's decision scope and fallback strategy
Build a runnable minimal agent for the core scenario to validate feasibility and results
Cover edge cases, add monitoring and logging, deploy, train and hand over documentation
AI Agent
An AI-driven testing platform for enterprise web systems: upload requirements, flows and prototypes and get executable test cases in minutes; agents then drive real browsers across roles and environments, capturing evidence at every step and producing three-state verdicts, a defect list and a per-model cost report.
Timelines vary by complexity: an AI agent runs from a POC to full delivery over weeks to months; a standard knowledge base ships within weeks; GEO foundation work usually takes 2–4 weeks.
| Project | Timeline |
|---|---|
| AI agent POC | 1 week |
| AI agent full version | MVP 2–4 weeks / full 6–12 weeks |
| Knowledge base (standard) | A few weeks |
| GEO foundation | 2–4 weeks |
We agree on acceptance criteria during requirements review and attach them to the contract, covering the feature list and key test cases. We demo against each item at delivery before maintenance begins.
You receive all source code and deployment docs at delivery; IP belongs to you. We keep reuse rights only to generic components and will sign an NDA.
Delivery includes a free maintenance period covering defects caused by our code, with the term set in the contract; annual maintenance can follow, and new features or changes from third-party API updates are scoped and quoted separately.