Artificial Intelligence
AI Search & RAG Development
Search that understands meaning, and AI answers grounded in your own content — the retrieval infrastructure behind every trustworthy AI feature.
Keyword search fails the moment users phrase things differently from your documents. Semantic search fixes that by matching meaning. And retrieval-augmented generation (RAG) goes further: instead of a list of links, users get a direct answer composed from your content, with citations to the source.
RAG is also the foundation under most serious AI products: it's how chatbots, copilots, and agents stay grounded in your truth instead of hallucinating. The quality ceiling of all those systems is the quality of their retrieval — which makes this the most leveraged engineering investment in an AI roadmap.
Good RAG is harder than the tutorials suggest. Chunking strategy, embedding choice, hybrid retrieval, reranking, freshness, permissions, and evaluation all determine whether users get precise answers or plausible noise. This is exactly the layer we specialise in getting right.
What We Build
AI Search & RAG: Our Offerings
Knowledge Base Search
Semantic search across your docs, wikis, tickets, and drives — one query, every silo, permission-aware.
RAG Pipelines
End-to-end retrieval-augmented generation: ingestion, chunking, embedding, hybrid retrieval, reranking, and grounded answer synthesis with citations.
Product & Catalogue Search
E-commerce and marketplace search that understands intent — 'warm jacket for trekking' finds the right products.
Enterprise Search Integration
Connectors for SharePoint, Google Workspace, Confluence, Notion, Slack, and custom systems, with source-level access control.
Retrieval Evaluation & Tuning
Measured retrieval quality on your real queries, with systematic tuning — for new builds or RAG systems that are underperforming.
Freshness & Sync Infrastructure
Pipelines that keep the index current as your content changes, so answers never come from stale documents.
What You Get
Delivered with Discipline
- Answers with citations, traceable to the exact source document
- Permission-aware retrieval — users only see what they're allowed to see
- Retrieval quality measured on your real queries, not benchmarks
- Index freshness as content changes, automatically
- A foundation your future chatbots, copilots, and agents build on
Technology
Tools We Work With
Technology choices are made per project — these are the tools we reach for most in ai search & rag work, and we'll explain the reasoning behind every recommendation.
FAQ
Common Questions About AI Search & RAG
What's the difference between semantic search and RAG?
Semantic search returns the most relevant documents for a query. RAG adds a step: a language model reads those documents and writes a direct answer, citing sources. Search gives you better links; RAG gives you answers. Most deployments offer both — answers when confidence is high, results when it isn't.
How do you handle document permissions?
Permissions are enforced at retrieval time: each query only searches content the requesting user is allowed to access, synced from your source systems' access controls. This is non-negotiable in our builds — a search system that leaks across permission boundaries is a security incident waiting to happen.
Our content changes constantly. Will answers go stale?
Sync pipelines watch your sources and update the index incrementally — typically within minutes of a change. Deleted or superseded content leaves the index just as fast, which matters more than people expect: answering from a withdrawn policy document is worse than not answering.
We tried a RAG demo and the answers were mediocre. Why?
Almost always retrieval, not the model: naive chunking, single-method retrieval with no reranking, and zero evaluation. Demos skip that work; production systems live or die by it. We start by measuring your current retrieval quality, then fix it systematically — it's very common for us to take over and rescue underperforming RAG builds.
Discuss Your AI Search & RAG Project
Tell us what you're trying to achieve and a specialist will get back to you within one business day.
- Free 30-minute consultation
- Quote within 48 hours
- Your idea stays confidential
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