Project Overview
Attorney Live, a growing legal technology provider, wanted to deliver faster, more accurate responses to legal questions within their tele-law platform. They faced a challenge of efficiently indexing legal documents and providing real-time responses. Avahi, an AWS Premier Tier partner, proposed a Generative AI–based solution on AWS that ingests, indexes, and retrieves data for targeted legal queries. This streamlined the company’s workflow, enhanced customer satisfaction, and reduced cost and complexity.
About the Customer
Attorney Live is a tech-forward legal services provider that specializes in on-demand, app-based tele-law solutions. Operating in the legal industry, it serves a wide client base by connecting users to attorneys and other critical legal resources through an intuitive and secure mobile and web platform.
The Problem
Attorney Live’s platform was experiencing challenges in quickly pulling contextual answers from large volumes of legal information. Manually indexing and searching through these documents was time-consuming, error-prone, and unsustainable as the company continued to scale. Furthermore, the need for multilingual support (Spanish to English, English to Spanish) and robust user feedback loops increased the complexity. Without addressing these issues, customers would continue to face longer wait times for critical information, undermining Attorney Live’s mission to bring timely legal guidance to its users.
Why AWS
AWS was the ideal choice for Attorney Live’s next-generation legal query solution because of its secure, scalable, and on-demand infrastructure that can handle large volumes of data and diverse application requirements. By leveraging services such as Amazon Bedrock and AWS Lambda, Attorney Live was able to incorporate sophisticated AI and machine learning capabilities without the overhead of managing complex infrastructure.
Why Attorney Live Chose Avahi
Attorney Live selected Avahi to lead this initiative due to Avahi’s proven track record in architecting end-toend cloud solutions with AWS AI services. Avahi’s deep expertise in generative AI workloads, combined with a history of delivering high-impact outcomes on short timelines, gave Attorney Live confidence that Avahi could design a solution aligning with both immediate and long-term business goals.
Solution
Avahi began by designing an event-driven serverless workflow on AWS. Key documents were placed in Amazon S3, which triggered AWS Lambda functions to generate embeddings and index the legal data. These embeddings were stored in a vector database to enable highly accurate similarity-based searches.
Using Amazon Bedrock, Avahi incorporated large language model capabilities to parse user queries, find relevant context from the embeddings, and produce precise answers. AWS Lambda functions also tracked user sentiment and captured conversation history. When dissatisfaction was detected, the system flagged these interactions for further review.
Additional Lambda services provided multilingual support so that both queries and AI-generated answers could be automatically translated between Spanish and English. Amazon API Gateway handled inbound requests from the Attorney Live application, routing each query to the appropriate AI pipeline. Finally, Amazon RDS was integrated to store final results, providing robust data consistency and analytics.
Key Deliverables
- Event-driven AI pipeline for real-time legal query processing
- Automated document ingestion and vector-based indexing
- Integration of multilingual capabilities (Spanish English)
- Real-time user feedback capture and dissatisfaction classification
- End-to-end solution documentation and handoff
Project Impact
By deploying the solution on AWS, Attorney Live now offers an enhanced, near-instant response system to users seeking immediate legal guidance. The integration of intelligent natural language processing and robust data indexing has improved user satisfaction and streamlined internal support processes.
- Completed the AI-driven legal query workflow in only three weeks
- Reduced total project costs to the customer to $0, thanks to AWS funding
