A custom AI layer that understands documents, cites sources and prepares routine reviews without uncontrolled black-box automation.
Document & Knowledge AI connects internal knowledge search, contract review, inbox triage, approvals and existing business systems. The system answers only with cited sources, marks uncertainty and routes critical decisions to a human for approval. Hosting, roles and data storage are planned so sensitive documents remain controllable.
Three modules form the knowledge layer: Knowledge Files index sources with metadata and permissions, a knowledge chat cites every answer, and a deep-knowledge graph links people, locations, contracts and projects across document boundaries.
Two modules form the workflow layer: contract review that checks documents against your business rules, and inbox triage that classifies, prioritises and routes incoming items to the right place.
Document AI becomes operational only when operations and integration are designed from the start: who may see which sources, which systems provide data, where approvals go, how answer quality is checked and who notices when costs or failure modes drift?
Yes. Permissions are checked before retrieval, not only after an answer is generated. Users only see sources, documents and results they are allowed to access.
Answers are tied to sources, uncertainty is surfaced and critical workflows require human approval. Test questions and failure types are reviewed before launch.
No. A clearly scoped starting set is better, such as contracts, policies or support emails. Additional document types can be added iteratively.
Typical integrations include DMS, SharePoint, email, ticketing, CRM, ERP, file shares and business applications. The key question is where AI can measurably reduce work in an existing process.
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