Skip to content

LLM & RAG Solutions

LLM & RAG Development Services

Put your company knowledge to work: assistants and search that answer from your documents, wikis and databases, with a source for every answer.

  • Answers with sources
  • Your data stays private
  • Evaluated for accuracy
5.0 on Clutch · 27 verified reviews (opens in a new tab)

What we offer

LLM & RAG Solutions services

  • Retrieval-Augmented Generation

    LLM answers grounded in your own content.

  • Document Ingestion

    PDFs, SharePoint, Confluence, databases and more.

  • Access Control

    Users only see answers from content they may access.

  • Evaluation

    Accuracy measured against real questions.

  • Fine-Tuning

    Tuned models when prompting and retrieval are not enough.

  • Private Deployment

    Run in your own Azure, AWS or on-premise environment.

How we deliver AI

From idea to production AI

  1. Use-case discovery

    We map where AI saves time or earns revenue, and agree how success is measured.

  2. Data readiness

    We review your data sources, access rules and privacy requirements.

  3. Fast feedback

    Proof of concept

    A working prototype on your real data, tested by your team.

  4. Evaluation

    Quality, safety and cost are measured against an agreed test set.

  5. Production rollout

    Secure integration with your apps, logins and workflows, with monitoring.

  6. Improve & scale

    Feedback loops, new use cases and cost optimisation as usage grows.

Technologies

Tools and technologies we use

Models

  • GPT
  • Claude
  • Gemini
  • Llama
  • Mistral

Retrieval

  • pgvector
  • Pinecone
  • Azure AI Search
  • Elasticsearch

Frameworks

  • LangChain
  • LlamaIndex
  • Semantic Kernel

Client reviews

What clients say about working with us

Verified reviews from founders and CTOs on Clutch.

5.0 27 verified reviews

FAQ

LLM & RAG Solutions: frequently asked questions

Straight answers to what clients ask us most.

Need advice for your project?

Every product is different. Talk to a senior engineer about your tech stack, timeline and team, and get honest advice on your next step.

Talk to an Expert
What is RAG?

Retrieval-augmented generation finds the most relevant passages in your content and gives them to the language model, so answers are accurate and cite sources.

Do we need to fine-tune a model?

Usually not. Good retrieval and prompting solve most cases; fine-tuning helps with specific formats or domain language.

Can RAG respect document permissions?

Yes. We filter results by the user's access rights before the model sees them.

How accurate are RAG assistants?

Accuracy is measured on a test set of real questions and improved before launch, and monitored afterwards.

Free discovery call

Have an idea? Let's turn it into AI-powered software.

Book a free discovery call with our experts. Share your idea and we will help you shape the scope, timeline and budget, under NDA.

  • Free consultation
  • NDA before we talk
  • Transparent estimate