Unlocking the Power of Data: How We Built Text-to-SQL with Agentic RAG at Rocket Mortgage

Why It Matters

By removing SQL barriers, Rocket Analytics accelerates decision‑making and expands data‑driven insight to non‑technical staff, delivering a measurable competitive edge.

Key Takeaways

• Agentic RAG turns natural language into accurate SQL queries
• FAISS vector store indexes metadata for efficient table retrieval
• Hybrid search plus Cohere re‑ranker cuts hallucinations
• Semantic and prompt caching lower latency and cost
• Multi‑agent orchestration enables cross‑domain insights

Pulse Analysis

Enterprises today sit on petabytes of siloed data, yet most business leaders lack the SQL expertise to extract timely insights. Rocket Mortgage’s Rocket Analytics tackles this gap by leveraging an agentic RAG architecture that treats database metadata as the only source of truth. By converting schema information into dense embeddings with Amazon Titan and indexing them in a FAISS vector store, the platform can swiftly surface the most relevant tables for any natural‑language query, sidestepping the need to expose raw data to the LLM and dramatically reducing hallucination risk.

The technical backbone blends semantic similarity with keyword triggers, ensuring critical tables are never missed. Retrieved candidates are then refined by Cohere’s BART‑based re‑ranker, which scores relevance before the prompt is assembled. Prompt engineering incorporates strict guidelines, few‑shot examples, and mortgage‑specific terminology, guiding the LLM to generate precise SQL statements. Additional layers of semantic and prompt caching reuse prior computations for similar questions, slashing latency and cloud‑compute costs while preserving accuracy at scale.

From a business perspective, the impact is profound. Teams across sales, operations, and finance can now pose questions like “What were loan closures last quarter?” and receive dashboards within seconds, eliminating days‑long analyst bottlenecks. The agentic framework also introduces sub‑agents for distinct domains, laying the groundwork for future cross‑domain queries without manual data stitching. As Rocket Analytics matures, its democratized data access model promises to become a strategic differentiator, fostering a culture where every employee can act on data‑driven insights without writing a single line of code.