Collate provides a semantic intelligence platform that unifies metadata from over 120 sources into a machine‑readable graph enriched with business glossaries, lineage, and quality metrics. The platform offers AI‑driven data discovery, natural‑language search, and automated governance features such as policy enforcement and data classification, enabling data teams to access trusted data and streamline compliance.
Funding
Funding not disclosed
Founders
Product
Problem
Data teams often contend with fragmented metadata across disparate systems, making it difficult to discover, trust, and govern data assets. Without a unified view, analysts and AI models struggle to understand data lineage, quality, and compliance, leading to slower insight generation and higher risk of errors.
Solution
Collate delivers a semantic intelligence platform that consolidates metadata from over 120 native connectors into a single, machine‑readable graph. The platform enriches this graph with business glossaries, lineage, and quality metrics, providing a consistent context for both humans and AI agents. Built on the open‑source OpenMetadata foundation, Collate adds enterprise‑grade features such as AI‑driven data discovery, conversational interfaces, and automated governance workflows. Intelligent agents can auto‑classify data, propagate policies, and generate documentation, reducing manual effort. Integrated dashboards and natural‑language query tools let users retrieve trusted data instantly, while the unified graph powers reliable AI model training and inference. The solution scales from small teams to enterprise deployments through flexible SaaS plans.
Target Audience
The platform is designed for data engineers, analysts, data stewards, and AI/ML teams in mid‑size to large enterprises that need reliable, searchable metadata and automated governance.
Features
- Unified semantic metadata graph (RDF‑aligned) that captures technical, business, and operational metadata across all assets.
- AI‑powered discovery with natural‑language search and relevance tuning, enabling self‑service data access.
- Automated end‑to‑end lineage extraction (including column‑level) from queries, pipelines (dbt, Airflow, Databricks) and dashboards.
- Continuous data quality profiling and test library (completeness, accuracy, freshness, anomaly detection) with AI‑generated test cases.
- Agentic governance: auto‑classification of PII/PII‑related data, policy enforcement, metadata propagation and reverse sync to source systems.
- AskCollate conversational interface and AI Studio/SDK for building custom, no‑code agents that automate documentation, quality, and compliance tasks.
- Collaboration workspace with shared definitions, RBAC, SSO, end‑to‑end encryption, and audit logs for secure, compliant usage.