What we implement
AI assistants for support and sales. LLM chatbots that answer from your knowledge base, qualify leads and escalate complex cases to humans. Integrated with your website, Telegram, WhatsApp and contact center.
RAG over corporate documents. Search and answers across policies, contracts, manuals, tickets. Employees ask in plain language and get an answer with a source link.
Document automation. Data extraction from invoices, contracts, IDs, forms. Classification of incoming emails and requests. Generation of standard documents.
Computer vision. Quality control on production lines, object and plate recognition, counting, safety video analytics.
Predictive models and BI. Demand, churn and default forecasting. Inventory and route optimization. Executive dashboards.
How implementation works
- Data and process audit, 1–2 weeks. Find 2–3 tasks with the highest impact, assess data quality.
- Pilot, 4–6 weeks. Working prototype on real data, metrics measured.
- Production rollout. Integrations, security, answer quality monitoring, staff training.
- Support. Quality drift monitoring, knowledge base updates, model fine-tuning.
Stack
Python, PyTorch, LangChain and LlamaIndex, vLLM, Qdrant and pgvector, OpenCV, ClickHouse, Apache Superset.