Description
Credal serves as the control plane for enterprise AI agents, enabling organizations to build, govern, and deploy AI agents and Model Context Protocol (MCP) servers efficiently. The platform is designed to be powered by your organization's data while adhering to stringent enterprise controls, ensuring both utility and security.
Read More
At its core, Credal features an Agent Registry that consolidates all internal and third-party AI agents and MCP servers. This registry allows for verification, publishing, and revocation from a single dashboard, effectively eliminating agent sprawl and providing built-in governance. With features like org-wide policies, such as mandating human approval for sensitive actions, and the ability to automatically mirror user permissions across systems, Credal ensures consistent application of rules.
Credal empowers teams to build AI agents with a no-code Agent Builder, facilitating the creation of agents for tasks like renewal call preparation or product requirement documentation. The Live Run feature allows for real-time understanding and execution of agent actions, including context gathering, tool invocation, and human-in-the-loop approvals before critical operations. Auditing is comprehensive, with all runs recorded and exportable to systems like Splunk and Datadog.
The platform supports granular access controls at user, team, and agent levels, ensuring that agents only access data and perform actions that users are permitted to. This includes auto-mirroring permissions from sources like Google Drive and SharePoint. Credal also offers tool-level controls, governing every action and integration agents can access, with options to package actions into governed MCP servers.
Security and compliance are paramount, with Credal infrastructure being SOC 2 Type 2 compliant and supporting both cloud and on-premise deployments. Permission syncing from over 50 sources ensures that agents operate within defined data access boundaries. Credal is built for both large enterprises and scaling startups, aiming to give every department access to governed AI agents while maintaining full visibility and control for administrators.
- CategoryAI Agent Builders
- DeploymentCloud, On-premise
Credal's Core Features
Unified Agent Registry for all AI agents and MCP servers
Built-in governance and compliance features
No-code Agent Builder for agent creation
Live Run for real-time agent execution and monitoring
Comprehensive auditing and traceability of all agent actions
Granular access controls at user, team, and agent levels
Automated permission syncing from connected data sources
Org-wide policies for consistent rule enforcement
Human-in-the-loop approval gates for sensitive operations
SOC 2 Type 2 compliant infrastructure
Support for cloud and on-premise deployments
Integration with over 50 data sources and systems
Model Context Protocol (MCP) server management
How to use Credal?
Configure: Connect your data sources and define initial policies.
Build: Use the Agent Builder to create custom AI agents.
Register: Add agents and MCP servers to the unified registry.
Govern: Set access controls, policies, and approval workflows.
Deploy: Distribute agents to specific users, teams, or the entire organization.
Monitor: Track agent performance, audit runs, and manage risks.
Optimize: Refine agent capabilities and workflows based on usage.
Credal's Use Cases
- Automate Sales Workflows
- Streamline Product Development
- Enhance IT Support
- Improve Customer Service
- Manage Compliance
- Facilitate Research
- Onboard New Employees
- Centralize Agent Management
