Lawrence AI
Developing an advanced SaaS platform with multi-agent AI architecture
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Lawrence AI is a virtual legal assistant, specifically designed for lawyers, law firms, and corporate legal departments. The platform transforms how users work with complex legal documents, legislation, and case law. It allows them to select relevant statutes and upload their own legal documents – from contract templates and interpretative opinions to court decisions. Users can then interact with these materials by asking precise questions and receiving instant, accurate, and source-backed answers. Lawrence AI dramatically accelerates legal research, streamlines document analysis, and saves valuable time that would otherwise be spent manually searching through texts.
Lawrence AI came with a clear product vision but needed a partner capable of turning that vision into a fully functional, scalable, and secure SaaS platform. This wasn’t about building a single feature – it required creating an entire ecosystem from the ground up.
The main challenges included end-to-end development (UI/UX, backend logic, and architecture), implementing advanced AI agents able to perform diverse tasks, and building a robust, automated infrastructure to ensure reliability. Just as critical was the need for close collaboration and co-development to transfer know-how to the internal Lawrence AI team.
- Need for complete SaaS development from A to Z
- Implementation of advanced multi-agent AI systems
- Building a robust, fully automated infrastructure
We acted as Lawrence AI’s technology partner and guided their vision through the entire development process. We designed an intuitive user interface, built the backend logic, and delivered a fully functional SaaS platform ready for its first users.
A key part of the solution was a custom-built multi-agent AI architecture. Each agent was specialized for a specific task (documents, databases, internet), and we applied advanced techniques such as RAG (Retrieval-Augmented Generation) to ensure precise and context-aware answers.
The platform was deployed on a modern, scalable infrastructure managed using GitOps principles. This ensured fully automated deployments, high reliability, and easy scalability. Throughout the project, we worked closely with Lawrence AI’s internal team, shared know-how, and ensured they were fully equipped to continue developing and maintaining the platform.
- Complete SaaS development from design to launch
- Multi-agent AI architecture with RAG techniques
- Modern, fully automated infrastructure (GitOps)
