Empathy Meets Efficiency: AI-Driven Email Automation for Legal Practices
Client:
Legal Company
Industry:
Legal Services
Technology and Platforms:
Python Azure functions, Azure OpenAI, Azure ecosystem, Salesforce integration
Background
A law firm specializing in mass lawsuits, particularly those related to health issues caused by toxic exposure, often deals with long litigation processes (5-7 years). Throughout this time, clients frequently ask for updates with vague questions like "Any updates?" or "How long?" Given the volume of inquiries and the complexity of the cases, responding manually to these requests is time-consuming and prone to inconsistency.
Initial Challenges
The firm needed a solution that could automatically generate empathetic, accurate responses to common inquiries without providing legal or financial advice. The goal was to free up human agents from repetitive tasks while maintaining a human-like approach in handling sensitive cases.
Solution
The solution implemented was a Generative AI (GenAI) application designed to generate automatic email responses based on the client's knowledge base. The key features of the solution included:
POC and Initial Exploration
We conducted a Proof of Concept (POC) to investigate the best GenAI approach, leveraging existing data such as email response scripts and relevant user information. We also integrated the solution with existing data sources to ensure compatibility.
Data Cleaning and Dynamic Context
We focused on data cleansing and API accessibility, incorporating company-specific data into the AI model. Instead of using an expensive Retrieval-Augmented Generation (RAG) approach, we implemented a dynamic context system, where the model selectively chose the files it needed for context. This solution proved to be highly efficient for our use case.
Salesforce Integration
We integrated the system with Salesforce to automatically trigger responses when new emails arrived, streamlining the workflow further.
Improving the model's understanding on long email threads, marking emails as not required to be answered.
Finally, we empowered the Case Success team to take ownership of the GenAI application. We trained them to improve the knowledge base and test prompts, enabling continuous optimization and scalability of the system.
Results and Added Value
- 99.9% emails were answered in under 5 minutes
- 96% of emails were automated
- Only 4% of emails had room for improvement (knowledge base, prompts, model following a better script)
During the Proof of Concept (POC) phase, the AI handled 46 out of 50 emails without any need for human intervention, which significantly lightened the load on human agents.
By automating common inquiries, the company ensured that every response was not only consistent and legally compliant but also empathetic. This helped maintain a high level of client satisfaction without losing the personal touch.
The AI’s internal feedback loop gave human case managers valuable insights, allowing them to fine-tune the knowledge base. This, in turn, improved the AI's response accuracy and deepened the firm’s understanding of recurring client concerns.
The AI’s ability to handle frequent, repetitive questions allows our client to scale effortlessly, without the need to add more human resources.
The AI’s systematic approach to asking key questions before generating a response ensures that communications are rooted in data, minimizing the chance of misinformation and enhancing the accuracy of client interactions.
