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Give every department their own AI agents connected to their knowledge, without ever losing visibility or control.
Set rules once, enforce everywhere.
Define what each person can do, from building to invoking.
Manage who can use, edit, and orchestrate each agent.
Govern every action and integration your agents can reach.
Full visibility into every agent action, with automated risk detection built in.
Credal inherits permissions across all connected source systems. When a user queries an agent, the response only pulls from sources that user has permission to access.
Sync permissions from Google Drive, Slack, Confluence, SharePoint, Salesforce, and 50+ sources
Automatically update permissions cache in real-time, synced with SSO
Granular and configurable access controls, no data leakage across permission boundaries
Build agents that reason across your data and take action in Salesforce, Jira, Slack, and every system your teams rely on. Every action or skill can be precisely scoped or given free reign.
Build agents with permissioned access to data, context, tools, and MCP servers
Connect agents to hundreds of approved actions across your tech stack
Stitch together complex workflows with specialized agents that work collaboratively
Read, write, and update across 50+ systems. Create tickets, update records, send messages, and more
Enforceable human-in-the-loop approval, audit logging, and access controls on every action
Add tools from third-party MCP servers with full Credal governance applied automatically
See how AI agents get built to automate workflows using your company's own data and tools.
Ravin from Credal.ai discussed the company’s agent registry and Model Context Protocol (MCP) with representatives from Customer X, including Joe from the security team. The conversation covered Credal’s capabilities around agent management, security, and integration with Customer X’s existing systems, leading to an agreement to explore a proof-of-concept collaboration within the next couple of weeks, pending the signing of an NDA.
Jessica Shen [2:10]: Thanks for taking the time today, Mike and Jennifer. How has your team’s experience been with Credal over the past quarter?
Mike Rodriguez [2:23]: Overall it’s been really positive. Our developers are finally able to find the documentation they need without having to ping people on Slack constantly. But I do have a few things I’d love to see improved.
Jennifer Walsh [2:35]: Yes, definitely. The search functionality is great, but we’ve run into some limitations.
Jessica Shen [2:42]: I’d love to hear about those. What specific challenges are you facing?
Mike Rodriguez [2:48]: So the biggest one is around our engineering tools. We use Linear for project management and GitHub for code, but Credal doesn’t connect to Linear yet.
From chat surfaces to workflow tools, Credal agents meet your teams where they already work, without adding extra platforms to manage.
Deploy to chat interfaces like Claude, ChatGPT, Cursor, or any MCP-compatible surface, Slack or API
Inherits enterprise context so tool calls are always accurate without redefinition
Eliminate agent sprawl with one unified registry
We are getting massive productivity ROI from Credal...I expected some usage from the agents, but I didn't expect to see people jump on it so quickly - even our non-technical teams have everything built on top of Credal.
It's rare to find an AI tool that actually delivers immediate business impact, but Credal does. 85% of our entire organization is now on board, and it's one of the most loved tools we have.
We saw the demo of the platform… being able to integrate into Google, Jira, and Slack. It was just that aha moment where I said, 'we found it, this is it.'
The focus for me has always been on helping humans do their job more effectively using AI…
The thing that Credal enabled us to do … was enable a lot of self-service ability to just create.
One platform for all agents. Full visibility for admins, full access for teams.