Metagraph offers a no‑code platform that lets teams build and deploy governed, agentic AI applications directly on their own data. The tool streamlines the creation of AI‑driven workflows that align with key performance indicators, enabling rapid deployment of custom AI agents without requiring extensive coding expertise.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations often struggle to create AI-driven applications that safely access proprietary data, requiring extensive coding, custom integrations, and complex governance to meet compliance requirements. This slows the deployment of AI solutions that could directly improve key performance indicators.
Solution
Metagraph provides a no‑code platform that lets teams assemble and launch agentic AI applications directly on their own data sources. Users connect data feeds, configure autonomous AI agents, and define output controls through a visual interface, eliminating the need for custom code. The platform enforces governance policies to ensure data privacy, compliance, and predictable behavior of AI outputs. Deployed apps can be shared with team members and integrated into existing workflows, enabling rapid iteration on metrics that matter to the business.
Target Audience
Primary customers are product, operations, and analytics teams in mid‑to‑large enterprises that need to build internal AI tools without extensive development resources.
Features
- Drag‑and‑drop interface for linking internal databases, APIs, and file stores to AI agents
- Pre‑built agent templates that can be customized to perform data extraction, analysis, and KPI reporting
- Built‑in governance controls that audit data usage, enforce output constraints, and log activity for compliance
- One‑click deployment to production environments with role‑based access for team members
- Real‑time monitoring dashboards that track app performance against defined business metrics