SpotDraft Data Ingestion Pipeline
Built a large-scale document ingestion pipeline processing millions of documents with LLM-based metadata extraction for a multi-agent legal AI system.
Pranav Pandey
Senior Applied AI Engineer at SpotDraft
From their time as
Senior Applied AI Engineer
SpotDraft • 2025
Overview
As part of the broader multi-agent system at SpotDraft, Pranav built the data ingestion pipeline that fed the platform's knowledge base. The pipeline processed large volumes of legal documents, handling chunking, information extraction, and metadata generation using LLMs before storing outputs in the production database.
The Story
As part of the broader multi-agent system at SpotDraft, Pranav built the data ingestion pipeline that fed the platform's knowledge base. The pipeline processed large volumes of legal documents, handling chunking, information extraction, and metadata generation using LLMs before storing outputs in the production database.
The pipeline was designed to handle the volume and variety of documents that enterprise legal teams work with, including contracts, filings, and internal documents of varying structure and quality. LLM-based extraction was used to pull structured metadata from unstructured document content at scale.
This pipeline was a foundational component of the overall system: the quality of what the agents could retrieve and reason over depended directly on how well the ingestion layer processed and indexed the source documents.