Audit & ROI
We map the current process, loss points, and calculate impact before development starts.
Business automation
Corporate neural net & AI assistant
Performer: Павел Стасиньский
Corporate neural net and enterprise AI assistant in your perimeter — without leaking data to public chats.
Describe the process or integration — we reply within 4 business hours.
B2B intent for a private corporate assistant — not a consumer chatbot.
Permissions and audit are part of the product.
Typical problems
- Staff paste data into public chats
- Need one assistant over policies
- Compliance and NDA requirements
- Cloud models blocked for some content
What you get
- Private contour architecture
- Models, access policies, SSO
- Knowledge base / CRM integration
- Monitoring and runbook
How we solve it
Architecture & integrations
We design workflow, CRM/ERP/API links, and an AI layer only where it delivers measurable value.
Delivery & handover
Production launch, documentation, team training, and optional SLA support.
Typical impact
−40–80%
manual work in the target process
2–8 wks
to first production release
3–6 mo
payback on a typical project
Package
Service details
Corporate AI assistant
Private LLM contour, access policies, integrations with internal systems.
| Price | from €5,000 |
|---|---|
| Timeline | 28 days |
| Format | Fixed estimate · remote delivery |
| Deliverables | Corporate neural net and assistant in a private contour — no data leakage. |
Trust
Reviews from Yandex
Public feedback from Yandex Services — same performer profile as the feed.
“Невероятный специалист. Откликнулся сразу, на протяжении всего процесса был на связи, работа выполнена качественно в минимальные сроки.”
“Павел — ас своего дела! Всё на высшем уровне, всегда на связи, оперативно отвечал на вопросы. Чувствовалось, что ему важен результат.”
FAQ
- On-prem or VPC?
- Both. Choice depends on data sensitivity and IT policy.
- Which models?
- GigaChat, YandexGPT, open-source, Claude via approved contour — by task.
- Timeline?
- Base contour 3–6 weeks; longer with RAG and CRM.