We developed an AI platform that automates contract data extraction for law firms while maintaining complete privacy through on-premise deployment.
We partnered with a vibrant start-up to develop a revolutionary platform that automates contract data extraction for law firms using advanced AI, while maintaining complete data privacy through on-premise deployment. The platform transforms how legal teams manage their knowledge base by combining sophisticated LLMs with a robust event-driven architecture.
We created a secure, enterprise-grade system that achieves 97%+ data extraction accuracy through fine-tuned LLMs and advanced NLP technologies. The platform enables law firms to automatically extract structured data from legal contracts without information ever leaving their environment, reducing deal profiling time by over 95%. The system processes documents through a sophisticated pipeline of microservices, utilizing cutting-edge AI models optimized for legal document understanding.
We teamed up with our customer’s data science team, integrating their multiple specialized LLMs into an efficient processing pipeline. The strategy combines an OCR process to convert documents into standardized text PDFs, a general-purpose LLM model that
handles high level document structure analysis and domain-specific LLM models for legal factoids extraction built on PyTorch and Unsloth allowing processing of both digital and scanned legal documents.
We implemented a real-time, event-driven distributed system using Redis Streams, replacing the original strategy based on polling. Using Protobuf and Web Socket connections, the new architecture connects an ecosystem of microservices that tackle each one of the different stages to ingest and process documents significantly improving scalability and responsiveness for complex workflows.
We developed two different state of the art UIs to ensure smooth usage of the platform. The admin interface is used by expert users to upload and tag contract samples. These are fed to a process that stochastically generates a training set with thousands of samples, that is used to fine-tune a dedicated LLM for a specific contract type. The end user UI allows law firms to easily upload contracts to the fine-tuned LLM models and extract structured data, making AI capabilities accessible to non-technical users.
Since joining the project in September 2024, we've helped transform the platform's architecture into a more robust and scalable system. The new event-driven design and AI processing pipeline have maintained the platform's impressive 97%+ accuracy in data extraction while improving system reliability and real-time processing capabilities. The platform continues to evolve, enabling law firms to revolutionize their knowledge management processes while maintaining complete control over their sensitive data.
We built a platform connecting indigenous communities with nature stewardship projects, creating quantifiable biodiversity credits for ESG.
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