Chat with us

Our Blog

Insights on RAG pipelines, semantic search and building AI products

What Is RAG? How Retrieval-Augmented Generation Works and How to Build a Production-Ready Pipeline

What RAG is, how it works step by step, how to build a production-ready RAG pipeline, and where each stage usually fails — with industry examples.

Intellara Team0 comments

Semantic Search Chunking Hybrid Search

Why Legal, Finance and Healthcare Documents Break Naive RAG — and How Structure-Aware Retrieval Fixes It

Fixed-size chunking and vector-only search fail on contracts, statements and clinical records. See how hybrid search, reranking and structure-aware chunking fix it.

Intellara Team0 comments

Security Permission-aware RAG PII

Private by Design: Permission-Aware, PII-Safe and Sovereign RAG for Regulated Industries

How to build RAG that respects permissions, keeps PII out of your vector store and can run air-gapped — with patterns for finance, healthcare, legal and government.

Intellara Team0 comments

RAG RAG Retrieval

Why RAG Fails at Retrieval, Not at the Model

Most disappointing RAG demos are blamed on the LLM. In practice the model is rarely the problem — the passages it was given are. Here is where retrieval breaks down and how to fix it.

Intellara Team8 comments

Semantic Search Hybrid Search Reranking

Hybrid Search and Reranking: Getting the Best of Keywords and Meaning

Keyword search is precise but literal; semantic search understands intent but can be vague. Combining them, then reranking, is how production systems get both.

Intellara Team12 comments

Industry Legal AI Finance

RAG for Legal, Finance and Healthcare: What Changes in Regulated Industries

Regulated documents have rules of their own: clauses that must stay together, tables that must add up, and sensitive fields that must never leak. Here is how RAG adapts.

Intellara Team6 comments

Engineering Knowledge Management Developer Experience

Keeping Engineering Documents Searchable as Projects Grow

Specs, runbooks, contracts and exported tickets pile up every week. A document search layer that stays in sync with your sources keeps knowledge usable instead of buried.

Intellara Team15 comments

Security PII Privacy

Protecting Sensitive Data Before You Embed It

Once sensitive values are embedded in a vector store they are hard to remove. Tokenising them before indexing keeps raw data out of the index entirely.

Intellara Team9 comments

Architecture Vector Database Qdrant

Managed or Bring-Your-Own Vector Database? Choosing a RAG Deployment Model

Hosted retrieval gets you moving fast; keeping vectors in your own database gives you control. Here is how to decide — and why the choice should not lock you in.

Intellara Team11 comments

Ready to operationalize AI in your business? Let us design and deploy the right solution together.

Get Consultation

Chat with us