Answers from your own knowledge, with the sources
We build retrieval-augmented generation (RAG) systems that answer from your documents and data, cite the sources they used, respect who may see what, and say so when the answer is not there.
- SourcesDocs, wikis, tickets, warehouse
- IngestStructure, metadata, versions
- RetrieveHybrid search + reranking
- PermissionsApplied before the model sees it
- AnswerCited, or an honest “not found”
RAG & Knowledge Systems
What we build
- 01
Internal knowledge assistants
Policies, procedures and support content - in a web app, Teams or an API.
- 02
Search that finds the passage
Semantic, keyword and hybrid search with reranking, tuned on real questions.
- 03
Assistants over structured data
Certified table definitions and joins first, SQL second, maths by deterministic tools.
- 04
Document ingestion
PDFs, scans and tables extracted with structure and source locations kept.
- 05
Permission-aware retrieval
Users never get answers built from documents they cannot open.
Results from our case studies
Selected work
Built for clients, running today
“The impact on our business results through the developed solutions has been immense. The AI-driven platform provided by Lexis Solutions formed the basis for the scalability of our business model, significantly cutting down operational costs. We are very fortunate to have partnered with them and look forward to future successes together.”
Emil PopovManaging Director, Kreston BulmarHow we work
From first workflow to production
- 01
Collect real questions
With the answers people expect - that becomes the eval set.
- 02
Ingest & structure
Connect sources, keep metadata, versions and permissions.
- 03
Test retrieval alone
Most quality problems start here, before generation.
- 04
Cite, then operate
Sourced answers, honest refusals, monitoring as content changes.
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Is it a fit?
Who we build this for
A good fit if you have
- People spend hours searching documents or asking colleagues
- Content that changes and must stay current
- Data with access rules that answers must respect
Probably not for
- Questions your documents do not answer
- A one-off search over a handful of files
Technologies we use
- Claude
- OpenAI
- Amazon Bedrock
- Google Vertex AI
- Hybrid search
- ChromaDB
- Model Context Protocol
- TypeScript
FAQ
Questions we often hear
Something else on your mind? Ask the engineers who would build it.
Ask us directlyNext step
Let’s talk about your project
Tell us what you are working on, and the engineers who would build it will get back to you.