AI use cases for Legal & Compliance
3 documented implementations
Lojas Renner Powers Retail AI Agents
Lojas Renner, Brazil's largest fashion retailer with over 20,000 employees, used the Databricks Data + AI Platform to build an AI agent factory. Using Delta Lake, Unity Catalog and Agent Bricks, it deployed an Internal Support Agent that automates HR and operational questions, a Labor Relations Agent serving over 430 users, an Executive Insights Agent, and Voice of the Customer Analytics, reducing response times, boosting agent retention and automating handling of most internal support calls.
Lojas Renner· BrazilDelta Lake · Unity Catalog · Agent Bricks +3Empowering Employees to Work Strategically Using Amazon Bedrock with BDM
Big Data Mining (BDM), a Brazilian company, built LOUIS, a bespoke generative AI model on Amazon Bedrock combining computer vision and natural language processing to process complex, unstructured corporate documents (contracts, powers of attorney) across more than 100 models and 15 industries. A large Brazilian financial institution deployed LOUIS to replace a team of 150 professionals manually evaluating over 40,000 unstructured processes per month for opening legal-entity accounts and contracting credit, standardizing interpretation criteria and reducing operational effort by more than 40%, an estimated $4.2 million in cost savings over five years. In insurance, LOUIS reduced life insurance claim processing from up to six months to just a few minutes by capturing required data in about 60 seconds. BDM reports documents are processed 85% faster than manual interpretation with 98% accuracy, and saved roughly 50% on development costs by building on Amazon Bedrock rather than writing the application from scratch.
Protect Crypto Assets with Governed AI
Elliptic, a blockchain analytics and digital asset compliance company, built a copilot on Databricks Agent Bricks to reduce compliance analyst workload by describing wallet activity, highlighting exposure paths, and producing neutral, report-ready risk narratives for financial institutions, crypto businesses and government agencies. MLflow tracing captures prompts, intermediate steps and final narratives for every interaction, and automated evaluation pipelines score responses for correctness, relevance and safety using LLMs as judges. Domain-specific safety guidelines distinguish between describing financial-crime typologies and inadvertently mentioning harmful activity, while custom safety scorers distinguish between explaining money-laundering patterns and promoting harmful activities. Elliptic reports compliance teams resolving high-risk screenings up to 2x faster and 40% less time needed to complete a Suspicious Activity Report.
EllipticAgent Bricks · MLflow · Databricks Foundational Models API +1