Knowledge audit
Review source quality, structure, permissions, and update frequency.
AI chatbots and RAG systems grounded in your knowledge base
Build assistants that answer from your documents, policies, product data, help center, or internal knowledge base with clear source grounding.
Starting from
€3 500
Production from €15 000
Client problem
Knowledge is scattered and support load grows
Customers and teams ask repeated questions, while the answers live across PDFs, help centers, Notion, websites, CRMs, and internal documents.
Solution
RAG assistant connected to trusted sources
We build retrieval-augmented AI assistants with indexed knowledge, source references, access control, feedback loops, and integration with support or internal workflows.
What is included
Chatbot and RAG scope
Data ingestion
Prepare documents, pages, records, embeddings, and search indexes.
Assistant logic
Prompts, retrieval rules, fallbacks, escalation, and safe answer behavior.
User interface
Website widget, internal chat, admin panel, or integration into your product.
Evaluation
Test answer quality, hallucination risk, coverage, and edge cases.
Deployment
Hosting, monitoring, analytics, and handover for ongoing content updates.
Process
From knowledge base to AI assistant
-
Collect
Identify sources, permissions, answer types, and support goals.
-
Index
Prepare content, retrieval strategy, and source-grounding behavior.
-
Build
Implement chat interface, integrations, guardrails, and analytics.
-
Improve
Review real questions, tune retrieval, and expand coverage.
Examples
Where RAG works well
Customer support bot
Answer product, billing, onboarding, and policy questions from trusted sources.
Internal knowledge assistant
Help teams search procedures, documentation, contracts, and operational knowledge.
Document Q&A
Search manuals, legal documents, research, specifications, or reports.
Product assistant
Guide users inside a SaaS product with contextual answers and next actions.
Want an AI assistant tied to real sources?
Share the type of knowledge base, target users, and required integrations to receive a practical estimate.