Technology
RAG Systems
Build RAG systems that stay accurate—retrieval, grounding, citations, and evaluation designed for real user questions and safe iteration.
Best For
Ideal use cases
Chatbots needing company-specific knowledge
Question-answering systems
Applications requiring factual accuracy
Knowledge bases with AI search
Customer support automation
What We Build
Projects we deliver
Knowledge base chatbots
Document Q&A systems
Customer support assistants
Internal knowledge search
Research assistants
Educational platforms
Legal document analysis
Technical documentation assistants
Ecosystem
Compatible tools & integrations
Seamless Integrations
Works with your existing stack
Use Cases
Recommended use cases
Customer support chatbots with product knowledge
Internal knowledge bases with AI search
Educational platforms with Q&A
Research tools analyzing documents
Applications needing accurate, sourced responses
Delivery
How we deliver
We design RAG systems with proper document chunking and indexing
Implement retrieval strategies balancing relevance and diversity
Use prompt engineering to incorporate retrieved context
Set up evaluation metrics and monitoring
Implement feedback loops for continuous improvement
FAQ
Frequently asked questions
RAG systems retrieve relevant documents and use them as context for language models. This provides factual, up-to-date information and reduces hallucinations compared to models relying only on training data.
We can use PDFs, Word documents, Markdown files, web pages, and other text formats. We parse and chunk documents appropriately, and can handle structured data like databases or APIs.
We evaluate RAG systems using metrics like retrieval accuracy, answer relevance, and user feedback. We test with sample queries, monitor response quality, and iterate based on results.
AI
Add AI on top of this stack
Two common AI services that pair well with this technology, plus the evidence-first buyer sprint.
Regional
Delivery considerations for your region
Data and risk discovery (Germany)
Privacy, security, residency, and regulatory requirements differ by workflow. We document the applicable data flows, roles, retention needs, and control owners before recommending an architecture.
The resulting proposal lists the controls and evidence that are actually in scope. It is not a generic compliance, certification, or legal-assurance promise.
- Map data sources, destinations, roles, and sensitive fields
- Record access, retention, logging, and deletion requirements
- Identify required security or procurement evidence before contracting
- Use an NDA or DPA only when the parties mutually execute it
Working model (Germany)
Exact live-overlap hours, response expectations, meeting windows, and escalation contacts are confirmed in the proposal for each engagement.
Written decisions, scoped milestones, and asynchronous updates reduce unnecessary meetings without implying an unagreed service level.
- Proposal-specific overlap and meeting windows
- Named owners for decisions and blockers
- Written scope, assumptions, and change decisions
- Milestone cadence agreed before kickoff
Commercial setup (Germany)
The contracting entity, proposal currency, invoicing cadence, payment terms, intellectual-property terms, and required vendor documents are agreed before work begins.
The Opportunity Sprint can establish the evidence needed to scope a production pilot; it does not pre-commit either party to a rollout.
- Contracting entity and currency confirmed in writing
- Milestones and acceptance criteria defined in the proposal
- Vendor-document requirements identified before signature
- Scope changes require an explicit written decision
Delivery controls (Germany)
Testing, observability, release, security, and handover controls are selected for the actual system risk rather than promised as a generic bundle.
Acceptance measures and production responsibilities are recorded before implementation so both teams know what evidence will support release.
- Risk-based testing and acceptance measures
- Release, rollback, and observability responsibilities
- Security controls tied to the agreed threat model
- Handover artifacts defined in the signed scope
Want to scope this properly?
Need RAG implementation services? Share your docs and workflows and we’ll propose next steps and milestones. EUR-based engagements.
We’ll review the context and reply with a practical next step.