How FinLegal and AWS Are Redefining Legal Workflows with Agentic AI

In an episode of AWS’s “Let’s Build a Startup”, FinLegal was featured as a case study in how cloud-native startups are transforming traditional industries through the power of agentic AI. Hosted by AWS’s Giuseppe and Letizia, the session explored how our platform is helping law firms drastically reduce the time and effort spent on manual document review, case management, and correspondence while maintaining the highest levels of compliance and accuracy.

Bringing Efficiency to Legal Case Management

FinLegal began with a mission to modernize how law firms manage complex, large-scale litigation. Our cloud-based platform, built entirely on AWS, supports firms across the UK, Europe, the US, and Australia. Traditionally, law firms have relied on manual, time-intensive processes for reviewing documents, communicating with clients, and drafting legal correspondence. FinLegal’s automation tools are changing that.

One of the key challenges we addressed is the creation of Demand Letters, documents that can take hours or even days to draft manually and can make or break a Personal Injury case. By integrating agentic AI workflows, FinLegal enables legal professionals to generate accurate, well-structured letters in under an hour. The AI analyzes multiple documents from medical reports to police statements and synthesizes the key details into a clear complete document ready for legal review. Human validation remains central to the process, ensuring that every output meets professional and ethical standards.

The Power of Agentic Architecture

During the episode, our CTO, Naeem Sarfraz, and AI Tech Lead, James Hughes, walked through FinLegal’s collaborative, multi-agent architecture, the backbone of our automation system. The design mirrors a real legal workflow, with each AI Agent handling a specific task:

A supervisor agent determines which sections a document requires, assigns tasks and checks for hallucinations and mistakes.
Sub-agents specialize in tasks such as summarizing medical evidence or extracting financial data.
A concluder agent integrates findings across sections.
Finally, a drafter agent produces a clean, compliant document, formatted using firm-specific templates.

This modular, “agents-as-tools” structure means the same framework can be reused for different legal jurisdictions and document types, improving efficiency and scalability. It’s a model built not just for speed but for reliability, transparency, and control.

Building with AWS

FinLegal partnered closely with the AWS Prototyping Team (previously mentioned in our blog), working alongside engineers to design, refine, and stress-test our approach. This collaboration helped us avoid common architectural pitfalls and integrate AWS-native tools seamlessly.

Built on .NET (C#), our system uses AWS Bedrock to access Anthropic Claude models, DynamoDB for data tracking, and a custom agentic orchestration layer that ensures secure, case-by-case isolation of client data. Every step, from model selection to token tracking is built with compliance and billing transparency in mind.

Human Oversight, AI Speed

A core principle in our approach is that AI doesn’t replace lawyers or paralegals, it empowers them. Every AI-generated document passes through human review before approval, and our platform includes built-in safeguards to flag potential inconsistencies or hallucinations. The result is faster outcomes without sacrificing quality or risk management.

Lessons for Startups

Reflecting on the journey, our team emphasized the importance of pragmatism and iteration. Building something real (quickly) creates invaluable learning opportunities. Engaging early with AWS experts helped us validate decisions, adapt fast, and maintain focus on solving real client problems rather than chasing hype. As James put it, “Agentic AI isn’t about replacing people; it’s about letting people do their best work faster.”

The Future of Legal Automation

This collaboration with AWS marks just the beginning. We continue to expand our AI capabilities across legal domains, personal injury to trust & estates, social security disability, mass torts and arbitration and employment law. The vision remains the same: to create intelligent tools that make legal work simpler and faster.

Author: Kelsey Wallace Mengel

Kelsey is an experienced legal professional specializing in optimizing intake processes with a focus on client retention, conversion, and personalized communication. She is skilled in training, quality control, and onboarding new case types, with a strong interest in leveraging technology for efficiency. A dedicated military spouse, Kelsey volunteers with the J.D. Military Spouse Network, supporting military families with legal needs.

FinLegal: Why Law Firms Need Agents & How We Built Them: An AWS Event