Recommind
Recommind provides an AI‑powered knowledge management platform that extracts text and entities from unstructured sources, builds a semantic knowledge graph, and enables intent‑based search across enterprise repositories. The solution includes a rule‑based compliance engine that continuously monitors the graph for policy violations and generates real‑time alerts, with role‑based access controls and immutable audit logs for regulatory traceability. It offers REST APIs and SDKs for integration with existing ECM, DMS, and BI tools, targeting large regulated enterprises.
Funding
Funding not disclosed
Founders
Founder details are not available yet.
Product
Problem
Enterprises often store critical information in disparate, unstructured formats—emails, PDFs, scanned contracts, and legacy documents—across multiple repositories. This fragmentation hampers accurate search, makes regulatory compliance monitoring labor‑intensive, and slows data‑driven decision making.
Solution
Recommind delivers an AI‑driven knowledge management platform that automatically extracts text, identifies entities, and builds a semantic knowledge graph linking content from heterogeneous sources. Advanced natural‑language processing (NLP) models generate contextual embeddings that enable precise, intent‑based search across all indexed assets. A rule‑based compliance engine continuously scans the knowledge graph for policy violations and flags risky documents in real time. The platform exposes RESTful APIs and SDKs for seamless integration with existing enterprise content management (ECM) systems, while role‑based access controls and immutable audit logs ensure data security and regulatory traceability. By unifying unstructured data into a searchable, governed knowledge base, organizations can accelerate insight generation and reduce manual compliance effort.
Target Audience
Primary customers are large enterprises in regulated sectors—such as legal, financial services, healthcare, and pharmaceuticals—that manage extensive collections of unstructured documents and require robust search and compliance capabilities.
Features
- Automated OCR and NLP pipelines that extract text, metadata, and entity relationships from PDFs, scanned images, emails, and other unstructured formats
- Semantic indexing using transformer‑based embeddings to support natural‑language queries with relevance ranking
- Dynamic knowledge graph that connects related documents, entities, and concepts across multiple repositories
- Configurable compliance rule engine that monitors the graph for policy breaches and generates actionable alerts
- Secure, role‑based access control and tamper‑evident audit logging for full regulatory traceability
- Extensible REST API and language‑specific SDKs (Python, Java, .NET) for integration with ECM, DMS, and BI tools
- Multi‑tenant SaaS architecture with data residency options and end‑to‑end encryption at rest and in transit