About Document RAG

Most RAG fails at ingestion — naive chunking breaks up tables, code blocks, and sections mid-thought. We use format-aware chunking (Unstructured.io + custom), preserve metadata (source, section, page), and filter retrieval by metadata for precision.

What We Deliver

Document ingestion pipeline
Format-aware chunking (PDFs, HTML, DOCX)
Vector embedding + storage
Metadata filtering on retrieval
Hybrid search (BM25 + vectors)
Reranking with Cohere/Voyage

Tools & Platforms We Use

LangChain / LlamaIndex

Unstructured.io

Pinecone

Cohere Rerank

Our Process

1

Audit & Assessment

We analyze your current state, identify gaps, and benchmark against competitors.

2

Strategy & Planning

We create a detailed action plan with priorities, timelines, and measurable KPIs.

3

Implementation

Our specialists execute the strategy with precision and attention to detail.

4

Monitor & Optimize

We track results, analyze performance, and refine continuously for improvement.

Document RAG