Smith & Associates Law Case Study

The Challenge

Smith & Associates, a mid-sized law firm specializing in corporate litigation, faced a growing bottleneck that was impacting their competitive edge and billable hours.

Their associates were spending upwards of 15 hours per week simply searching for past case precedents and relevant internal documents across a database of over 50,000 PDFs—including scanned contracts, court filings, deposition transcripts, and historical case files.

Pain Points

Keyword Search Limitations Traditional search was missing contextually relevant documents that didn't contain exact keyword matches

Inefficient Manual Review Attorneys had to manually review dozens of documents to find specific clauses or precedents

OCR Quality Issues Many historical documents were scanned PDFs with poor OCR quality, making them unsearchable

The Solution

GoCustom AI deployed a secure, private Retrieval-Augmented Generation (RAG) system tailored specifically for the legal domain, ensuring complete data privacy while delivering powerful semantic search capabilities.

Technical Architecture

1

Data Ingestion & Processing

Securely indexed the entire 50,000+ document repository with advanced OCR technology for scanned PDFs, ensuring full text searchability across all historical documents.

2

Semantic Vector Search

Implemented a semantic search engine that understands legal concepts and context, not just exact keyword matches. Queries like "breach of fiduciary duty precedents" return relevant cases even if they use different terminology.

3

Private LLM Integration

Connected a self-hosted Large Language Model to summarize findings and draft memos. All processing happens on-premise—no client data ever leaves their secure environment.

Security & Compliance First

The entire system is deployed on-premise within Smith & Associates' existing infrastructure. All data remains under their control, meeting strict attorney-client confidentiality requirements and bar association compliance standards.

Implementation Timeline

The project was rolled out in three carefully planned phases over 6 weeks:

1

Audit & Security Review

Week 1-2

Conducted comprehensive security audit of the proposed architecture. Ensured compliance with attorney-client privilege requirements and bar association standards for data handling.

2

Indexing & Fine-Tuning

Week 3-4

Processed the entire document corpus with enhanced OCR. Fine-tuned retrieval parameters for legal terminology and trained the system to understand firm-specific case categorization.

3

Deployment & Training

Week 5-6

Installed the interface on associate workstations. Conducted hands-on training sessions demonstrating advanced query techniques and best practices for legal research workflows.

The Results

90% Reduction in Research Time

Associates can now find relevant precedents in minutes rather than days. The system not only retrieves documents but highlights the specific paragraphs relevant to the query, with citation-ready references.

Productivity Gain

13.5hrs/week

Per associate saved on research tasks

Response Quality

95%+

Accuracy on retrieved precedents

Client Satisfaction

↑35%

Faster turnaround on opinions

Business Impact

Faster Response Times: Legal opinions that previously took 2-3 days now delivered within hours
Reduced Billable Research Hours: Clients pay less for administrative tasks, improving satisfaction and retention
Associate Morale: Junior attorneys report higher job satisfaction focusing on strategic work rather than tedious searches
Competitive Advantage: Ability to take on more cases with the same team size

"The AI research assistant has been transformational for our practice. What used to take days now takes minutes. Our associates can focus on high-value analysis rather than hunting for documents. The system pays for itself every single week."

JS

James Smith

Managing Partner, Smith & Associates Law

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