Document ingestion
Designed around clear interfaces, documented decisions and maintainable implementation.
Retrieve · Ground · Cite
Make business knowledge easier to find and use
Secure knowledge assistants that answer questions using approved documents and business data with citations.
The business problem
Build for the real operating context
Important knowledge is often scattered across documents, portals and teams. Retrieval-augmented generation can make it conversationally accessible while retaining sources and access controls.
We align user needs, technical constraints and business outcomes before selecting architecture or implementation tools. The result is a solution designed to keep working beyond the initial release.
What we provide
Capabilities for rag systems
A focused engagement can use one capability or combine several into an end-to-end delivery.
Semantic and hybrid search
Designed around clear interfaces, documented decisions and maintainable implementation.
Embeddings and vector retrieval
Designed around clear interfaces, documented decisions and maintainable implementation.
Source citations
Designed around clear interfaces, documented decisions and maintainable implementation.
Role-aware access
Designed around clear interfaces, documented decisions and maintainable implementation.
Quality evaluation
Designed around clear interfaces, documented decisions and maintainable implementation.
Typical use cases
Where this work creates value
- ✓Internal knowledge assistant
- ✓Policy assistant
- ✓Product support assistant
- ✓Technical documentation assistant
- ✓Sales knowledge assistant
- ✓Customer service knowledge assistant
Architecture view
Connected by design
Business outcome↓
Experience & workflow↓
RAG Systems↓
Data, APIs & controls↓
Cloud & operations
Delivery approach
Progress in visible, testable increments
Discover
Clarify outcomes, constraints, users and the current technical landscape.
Define
Shape the architecture, delivery roadmap and measurable acceptance criteria.
Build
Deliver in visible increments with testing, review and practical documentation.
Improve
Measure production behaviour and evolve the solution as needs change.
Technology capabilities
LLM APIsEmbeddingsVector databasesPostgreSQLPythonDocument parsingEvaluation datasets
Questions
Frequently asked
Useful starting points. A discovery conversation will make the answer specific to your situation.
What is RAG?+
Retrieval-augmented generation finds relevant information from approved sources and supplies it to a language model so responses can be grounded in business context.
Can RAG work with our internal documents?+
Yes. Ingestion can be designed for approved documents, knowledge bases and structured business data, with source-specific processing.
What file formats can be supported?+
Common formats such as PDF, Word, HTML and plain text can be supported. The right parsing approach depends on document structure and quality.
Can access be restricted by user role?+
Yes. Retrieval can enforce document- and metadata-level permissions so users only receive context they are authorized to access.
Does RAG eliminate AI hallucinations?+
No. It can reduce unsupported answers by grounding responses, but responsible deployment also needs evaluation, guardrails, citations, monitoring and human review where appropriate.
Can it connect with existing business software?+
Yes. A knowledge assistant can integrate through APIs, identity providers and approved data connectors.
Related services
Connect the next part of the system
Generative AI
LLM-powered applications, copilots and document workflows with evaluation, guardrails and cost controls built in.
Explore →AI Agents
Goal-driven assistants that use approved tools and APIs within explicit boundaries, observability and human oversight.
Explore →API & Integration
Well-designed APIs and reliable integrations across internal software, SaaS platforms and external services.
Explore →Let's make it practical
Ready to explore rag systems?
Tell us what you're trying to solve. We'll help you turn the problem into a practical technology roadmap.