RAG & enterprise knowledge
Retrieval over financial research that returns the exact paragraph
Analysts ask in plain language and get the exact passage, table or figure, with its source.
- Status
- ● Live in production
- Client
- Private
- Practice
- Engineering
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The problem
Keyword search failed across filings, spreadsheets, decks, research notes and live market data. Analysts needed exact values, not a summary.
What we built
- A
Parsing and embedding for every format, with finance-specific metadata attached to each chunk.
- B
Semantic retrieval followed by metadata-aware reranking and filtering, so answers come back as exact paragraphs, tables and values.
- C
Separate namespaces and access rules for proprietary sources, with agents that orchestrate multi-step research questions.
Stack
- Vector search
- Metadata filtering
- Reranking
- Multi-agent orchestration
Designed and built by our senior engineers. The architects you'd meet on a first call are the people who built this.
Client names stay private. Every system here is real and in production, and we're glad to walk you through the ones relevant to you on a call.
Office hours
Working on something similar?
Your first call is with a senior lead who will own the work. Send a few lines about the product and what's hard about it.
- Your point of contact
- Vidit Galav, Director
- Follow
- Delivery
- Our team works across US, European, APAC and Middle East hours.