Intellara is an AI product development company specialising in RAG pipelines and semantic search for legal, finance, healthcare and more. Our product troveGEN gives AI apps the perfect context, and helps engineering teams keep ever-growing project documents searchable.
Every knowledge-intensive field — law, finance, healthcare, government, engineering — holds its expertise locked in documents. We build the RAG pipelines and semantic search that make those documents accurately searchable by people, AI apps and AI agents.
troveGEN is our RAG pipeline and search API. Upload, crawl or sync your documents and it reads them, protects sensitive data, and returns the right passages — with sources — to your app or AI agent, only for the people allowed to see them.

Turn any document into accurate, private AI search. One API gives AI apps the perfect context to generate from, and gives engineering teams a way to keep every growing pile of project documents searchable.
Whether you are building an AI product or running an engineering organisation, the problem is the same: the right document content, in the right place, at the right time.
LLM answers are only as good as the passages behind them. troveGEN runs the whole retrieval stack — hybrid search, reranking, permissions, citations — behind one API call, so your app or agent generates from exactly the right context and says so when the answer isn't there.
Specs, runbooks, contracts, tickets exports and customer files pile up every week. Connect your sources once and troveGEN keeps them indexed and in sync — versioned, access-controlled and searchable by words or by meaning, however big the archive gets.
Wherever expertise lives in documents, RAG and semantic search turn it into answers you can cite. Here is where teams put it to work.
Search contracts, case law, statutes and policies by meaning and by exact citation, with every answer pointing back to the clause or paragraph it came from.
Ask questions over bank statements, filings, invoices, policies and loan documents — tables stay intact so totals are computed from the rows, not guessed.
Find the right guideline, discharge summary or drug monograph with sensitive data protected before indexing. Retrieval support for staff — not clinical advice.
Make circulars, notifications, tenders, schemes and acts searchable by number, date, department and meaning — in the languages citizens actually use.
Give guest-facing assistants and support teams grounded answers from property fact sheets, rate cards, policies, brochures and SOPs.
Ground lesson companions in curricula, rubrics and institutional policy so students get answers that point back to the source material.
Keep specs, runbooks, API docs, contracts and exported tickets searchable as the pile grows — for engineers, support teams and coding agents alike.
Give support agents and customer-facing assistants accurate answers from help centres, product manuals, policies and past resolutions, with sources they can verify.
Beyond troveGEN, we build custom AI products and retrieval systems with teams that need more than an off-the-shelf pipeline.
Most software companies are adding AI layers to existing products. We designed the architecture first, then built the product around it — meaning intelligence is structural, not cosmetic.
Short, direct answers to the questions teams ask us most.
Intellara Technologies is an AI product development company in Bengaluru, India, specialising in RAG (retrieval-augmented generation) pipelines and semantic search for legal, finance, healthcare and other knowledge-dense domains. Its product, troveGEN, is a RAG pipeline and search API that gives AI apps and agents accurate, cited context.
RAG is a technique where a language model is given passages retrieved from your own documents at question time, so its answers are grounded in evidence instead of memory alone. A RAG system reads and chunks documents, indexes them for keyword and semantic search, retrieves and reranks the best passages for each question, and then generates a cited answer.
troveGEN is Intellara's RAG pipeline and search API for AI apps and agents. It reads PDFs, scans, spreadsheets, web pages and email, protects sensitive data, and returns the right passages with sources, only to people allowed to see them. It runs fully managed or inside your own vector database, including air-gapped.
Finance, healthcare, legal, government, hospitality, education, customer support and software or engineering teams. troveGEN includes industry settings for finance, healthcare, legal, hospitality, government and education, so tables, clauses, clinical lists and reference numbers are retrieved intact.
Yes. troveGEN supports bring-your-own vector databases (Qdrant, Pinecone, pgvector, Postgres), your own embedding and reranking models and keys, and a fully air-gapped mode that makes no outbound requests when local models are used.
troveGEN starts with a free trial of 500 pages. Fully managed troveGEN-Z plans start at $25 per month, bring-your-own-vector-database plans start at $89 per month, and Sovereign deployments are quoted. Annual billing is ten times the monthly price, so two months are free. See trovegen.com/pricing for current limits.
Whether you're building an AI app that needs the perfect context, an engineering team whose documents keep piling up, or an organisation in law, finance or healthcare with a corpus that deserves AI — let's talk about what a RAG pipeline and semantic search can do for you.