Dawiso AI Context Layer

Key Features

• •Automatic Data Catalog: Scans your data landscape with 40+ connectors to automatically discover assets, map dependencies, and build a comprehensive catalog, providing AI with a unified view of all data sources without manual effort.
• •AI-Generated Business Glossary: Uses AI to write business descriptions, suggest ownership, and classify data assets, turning raw metadata into documented knowledge ready for human review in hours instead of weeks of manual writing.
• •Interactive Data Lineage: Automatically traces and visualizes how data moves, transforms, and connects across systems, applications, and reports, giving AI agents understanding of data provenance and relationships.
• •MCP (Model Context Protocol) Server: Connects any AI agent or LLM like Claude or Copilot to your governed context in real-time via an open standard, allowing AI to query trusted business terms, lineage, and metadata directly.
• •Intelligent Relationship Mapping: Discovers and maps connections between business terms and data assets automatically, showing AI how different elements relate within your enterprise landscape.
• •Unstructured Data Governance: Manages both structured and unstructured data on a single platform, ensuring AI has context for all data types, including documents and files beyond traditional databases.
• •Human-in-the-Loop Governance Workflows: Incorporates approval workflows, stewardship roles, and quality checks where AI generates context for team review, maintaining accuracy and trust in business definitions.
• •Rapid Deployment: Enables most teams to have a working data catalog and business glossary within a single day, with full context layer deployment typically completed within one to two weeks for fast time-to-value.

Use Cases

• •Preventing AI Hallucinations: When AI agents lack business context, they invent facts. The Context Layer provides governed definitions and lineage, so AI answers are grounded in verified metadata, eliminating guesswork and manual debugging.
• •Ensuring Regulatory Compliance: AI accessing sensitive data without governance creates audit risks. The platform provides traceable lineage and approval workflows, giving regulators justified, documented answers instead of 'the model decided.'
• •Accelerating Data Catalog Projects: Building a traditional data catalog can take months. Dawiso automates discovery and documentation, delivering an AI-ready catalog in weeks, speeding up AI project timelines significantly.
• •Unifying Business Terminology: Business terms are often scattered. The AI-generated glossary creates a single source of truth, ensuring all AI agents and reports interpret 'revenue' or 'customer' consistently across the organization.
• •Connecting Multiple AI Tools: Enterprises use various AI agents like Claude and Copilot. The MCP Server integrates them all with one protocol, providing each with the same governed context without custom integrations.
• •Governing Unstructured Data for AI: AI needs context from documents and files. The platform governs unstructured data alongside structured sources, giving AI a complete view of enterprise information for more accurate analysis.

Who is this for?

Data leaders, data engineers, business analysts, domain experts, and security consultants in enterprises implementing AI projects, particularly in regulated industries like finance and insurance. The platform is designed for both technical users who set up connectors and business users who contribute definitions, requiring no coding for day-to-day operations. It is trusted by leading enterprises such as Société Générale, Komerční banka, ČEZ Group, and Nationale-Nederlanden.