24/7 help for employees and customers: product questions, internal policies, order status, hand-off to a human when confidence is low. Messengers (Telegram, VK, MAX) or embedded web widgets—shared logic with chat bots and automation.
Engagements around ai assistants and chat bots usually start with a short discovery call, a written scope outline, and a first milestone you can demo to stakeholders within weeks—not months of silent development.
When this fits
Teams usually request ai assistants and chat bots when an off-the-shelf product does not match process, compliance, or integration constraints.
- Operations outgrow spreadsheets and informal tools around ai assistants and chat bots
- You need a stable system with roles, audit trail, and predictable releases
- Internal or external APIs must exchange data without manual re-entry
- Leadership wants measurable delivery milestones, not a single big-bang launch
What is included
- Discovery workshop: goals, constraints, existing systems, success metrics
- Architecture sketch and backlog sliced into vertical milestones
- Implementation with code review, staging environment, and handoff notes
- Launch support and a short hypercare window after go-live
Stack and approach
For AI implementation we rely on LLM, RAG, chatbots, OCR, document AI, forecasting, TypeScript, Node.js, Python, ERP APIs, 1C, data security, process automation. We prefer explicit types, small deployable increments, and observability hooks (structured logs, health checks) so your team can operate the system after handoff.
Example from practice
Related deliveries: thinklens-bot, cursor-telegram-integration. These projects illustrate how we structure UI, APIs, and data for production use—not slide-deck prototypes.
Timeline and format
A focused MVP often ships in 4–8 weeks depending on integrations and compliance. We work in 1–2 week iterations with demoable increments; scope changes are tracked openly so estimates stay honest.
