Legal Services | AI Document Intelligence & Analytics
Reduction in document retrieval and search time
Improvement in drafting efficiency for standard document types
About
Sterling Legal Group is a mid-sized legal firm with practice areas spanning corporate litigation, contract law, and regulatory compliance. The firm manages a significant volume of active matters simultaneously, with a case filing repository that had grown to approximately 3 terabytes of documents stored in SharePoint — spanning case filings, precedents, correspondence, contracts, and internal research documents accumulated over many years of practice.
Industry
Legal Services | AI Document Intelligence & Analytics
Company size
100 – 500 employees
Founded
2000
The Company
A legal firm whose document infrastructure had not scaled with its growth
Sterling Legal Group is a mid-sized legal firm with practice areas spanning corporate litigation, contract law, and regulatory compliance. The firm manages a significant volume of active matters simultaneously, with a case filing repository that had grown to approximately 3 terabytes of documents stored in SharePoint — spanning case filings, precedents, correspondence, contracts, and internal research documents accumulated over many years.
As the repository grew, so did the friction of working with it. Finding relevant precedents or filing history for a new matter required experienced lawyers to manually search through folder structures and document names — a process that was time-consuming, inconsistent, and heavily dependent on individual institutional knowledge. A junior lawyer new to the firm had virtually no ability to navigate the repository effectively without senior guidance.
The challenge
Two parallel inefficiencies compounding the cost of document work
Document retrieval and document drafting presented parallel inefficiencies that together consumed a significant proportion of billable capacity. On retrieval: finding relevant precedents or filing history required experienced lawyers to manually search through a repository that had no semantic search capability — navigation depended on knowing folder structures and file names, rather than the content of the documents themselves.
On drafting: standard legal documents — NDAs, engagement letters, court filings, compliance certificates — were being drafted from scratch or by manually adapting previous versions, with no mechanism for ensuring the resulting documents reflected the firm's current standard terms and formatting requirements. Review cycles were extended by the need to correct formatting inconsistencies and non-standard language that crept in through the manual drafting process.
The partners had long acknowledged that a significant proportion of time billed to clients for document retrieval and first-draft preparation was not genuinely value-adding. It was the overhead of working with a document infrastructure that had not scaled with the firm's growth — and it was visible to clients in the form of time charges that were difficult to justify.
The Solution
An AI document assistant built on a RAG architecture integrated with SharePoint
Seven Billion developed an AI document assistant that integrated directly with the firm's SharePoint repository, built on a Retrieval-Augmented Generation (RAG) architecture using Llama 4 Maverick on AWS Bedrock.
The system had three core capabilities: natural language querying, allowing lawyers to ask questions in plain language and receive accurate, cited responses drawn from the document repository, with source documents surfaced for review; document summarisation, generating structured summaries of any document or document set, extracting key terms, dates, parties, obligations, and risk factors in a standardised format that significantly accelerated document review; and template-based drafting, generating first drafts for standard document types based on the firm's standard templates, incorporating matter-specific details and flagging clauses where non-standard treatment was required.
The system was deployed through a web interface accessible to all fee earners and integrated with the firm's matter management system to enable matter-specific document scoping. An audit trail was maintained for all queries and generated documents, supporting the firm's quality and compliance requirements. The three-terabyte repository — previously navigable only by experienced fee earners with deep institutional knowledge — became fully queryable by anyone in the firm.
The Results
70% faster retrieval, 50% improvement in drafting, and a transformed junior experience
Document retrieval time reduced by 70% on average, with the most significant gains on complex multi-document queries that previously required hours of manual search and review. Drafting efficiency improved by 50% for standard document types, with the time from instruction to first draft reduced from hours to minutes for NDAs, engagement letters, and standard compliance certificates.
Document formatting consistency improved to near-100% for AI-assisted drafts, eliminating the review cycle overhead caused by formatting inconsistencies in manually prepared documents. Junior lawyers reported a significant improvement in their ability to navigate the repository and contribute to matters independently — reducing the senior supervision time required for routine document tasks.
The engagement changed how the firm thought about the value of its accumulated knowledge. Three terabytes of precedents, filings, and research that had previously been inert institutional memory became an active, accessible asset — one that every member of the firm could draw on from their first day.
The assistant did not replace any of our lawyers — it made all of them significantly more productive. The time we have recovered from document search and first-draft preparation is now spent on the work that actually requires legal judgment. That is the right trade.
Managing Partner, Sterling Legal Group
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