A Legal Team’s Entire Document Corpus, Answered in Seconds
The Client:
A legal services firm managing a large and growing repository of client documents: contract drafts, signed agreements, emails, spreadsheets, public filings, and multimedia files. A dedicated team of counsels was responsible for answering queries by manually reviewing this corpus.
The Engagement:
SSI built a GenAI-powered legal assistant using a Retrieval-Augmented Generation (RAG) architecture, enabling the counsel team to query the full document corpus through a conversational interface with source-attributed, citation-ready answers.
The Challenge:
The document repository spanned multiple formats; PDF, Excel, Word, audio, and video making manual search slow and inconsistent. Finding a specific clause or precedent could take hours.
Large Language Models offered a solution in principle, but couldn’t handle the full document corpus in a single context window. A system was needed to identify the most relevant documents before querying the model.
The firm also needed auditability: every answer had to be traceable to a specific source document, with citations the counsel team could rely on in client-facing settings.
The Solution:
SSI implemented a RAG pipeline that ingests the full document corpus across all formats and indexes it for semantic retrieval. When a query arrives, the system identifies and retrieves the most relevant document chunks before passing them to the language model.
The LLM generates responses grounded in retrieved content, with explicit citations and source references for every claim. This eliminates hallucination risk and gives counsel a verifiable answer trail.
Domain-specific tuning was applied to handle legal terminology and document structures, improving retrieval accuracy on specialized queries around jurisdiction, liability, indemnity, and contract terms.
The Impact:
Query resolution time dropped from hours to seconds for the majority of standard lookups. The counsel team redirected the time saved toward higher-value advisory work.
The citation layer also reduced the risk of errors in client communications, every answer was backed by a traceable source, not a counselor’s memory.
