AI readiness audit
Data, processes, risks. ROI by scenario: support, documents, sales.
Enterprise AI implementation is not a ChatGPT pilot — it is a production system: architecture, integrations, monitoring, compliance. AI makes sense when process and data are already structured.
We deploy corporate assistants, document RAG, CRM and support agents — in your perimeter or isolated cloud.
We start with audit: where AI delivers ROI and where workflow without LLM is enough.
When it makes sense
- ChatGPT pilot does not scale to a department
- You need corporate AI inside your perimeter
- You need implementation with team handover
Outcome
- Architecture and model selection
- CRM, document and messenger integrations
- MLOps, monitoring, documentation
How we deploy enterprise AI
Architecture
Model (YandexGPT, GigaChat, private LLM), RAG, API, CRM and messenger integrations.
Production
MLOps, logging, guardrails, team handover. Not a demo — working system.
When AI pays off
−40%
L1 support load
3–6 mo
typical RAG assistant payback
on-prem
data stays in your perimeter
Package
AI implementation
Architecture, LLM integration, CRM/messenger connectors, production deployment, and team handover.
Service details →Featured case
Kaspersky AI Assistant
Hundreds of repetitive product and license questions.
LLM + documentation RAG + escalation.
Faster typical cases, more time on complex ones.
Case studies
Email AI Assistant — Kaspersky
−50% повторных обращений L1
Консультанты быстрее закрывают типовые обращения, единообразно отвечают на вопросы о продуктах и тратят больше времени на сложные инциденты и апсейл.
View case study →
Yandex Telemost Agent — ИИ для встреч и продаж
Автоматические итоги встреч в CRM
Команда экономит время, быстрее обрабатывает итоги встреч, не забывает договорённости и повышает качество сопровождения клиентов и продаж.
View case study →Enterprise AI FAQ
- When does AI make sense vs workflow?
- Workflow for rules and routes. AI for unstructured text, classification, dialogs. See our guide.
- ChatGPT or own model?
- For corporate data — private LLM or YandexGPT/GigaChat in your contour.
- Cost?
- Audit from €1,500. Implementation from €5,000 depending on integrations and knowledge volume.
Contact
Discuss your project
Describe the process or integration — we reply within 4 business hours.