AI-powered compliance. Incident reports to structured regulatory filings, in seconds.

RadarFirst helps organizations manage privacy incidents and regulatory compliance across dozens of data privacy laws worldwide. Their clients needed faster, more accurate reporting workflows capable of handling diverse regulatory frameworks, but the existing process relied heavily on manual data entry and human interpretation of incident reports.

The key challenges were formidable: extracting structured information from unstructured natural-language incident reports, ensuring accuracy and compliance across multiple regulatory schemas simultaneously, and building an AI system reliable enough for production use within strict data governance requirements.

RadarFirst needed an engineering partner with deep AI expertise who could design, build, and deploy a production-grade AI system, not a proof of concept.

We designed and deployed a custom solution leveraging AWS Bedrock, SageMaker, and LangChain. The system applies retrieval-augmented generation (RAG) and natural language processing (NLP) to automatically extract relevant entities from incident reports and populate regulatory compliance forms.

To ensure precision and scalability, we implemented a hybrid transactional and analytical architecture, integrating event-driven streaming, validation layers, and multi-schema regulatory mapping. The AI system was built with production-grade reliability from the start: not a demo, not a prototype.

The result: an AI chat assistant that converts natural-language incident reports into structured compliance forms, reducing manual workload and human error in incident intake and risk categorization. RadarFirst secured early adopters and positioned themselves as an AI-driven compliance leader.