Today, we’re announcing AI Access Management: a unified control plane for managing access to AI tools and data used by employees, in personal assistants, and enterprise agents. End users get secure access in seconds while security gets full visibility and policy enforcement over every tool call. No credentials on laptops. No multi-day setup processes or helpdesk tickets required. No more dependencies on vibe-coded MCPs installed locally on laptops.
It started with a simple problem
This product started with Claire, a marketing director here at ConductorOne. She writes about technical topics, analyzes SEO / GEO performance, and drives our web traffic. She uses Claude Desktop and knew that AI could help her do her job more efficiently if she had the tools and data access.
Claire saw a blog post about connecting Claude to Google Analytics. She tried to follow the setup instructions: install Python dependencies, create a Google Cloud project, enable the Analytics API, create a service account, download JSON credentials, configure a local MCP server, restart Claude. She got stuck at step one and gave up.
The next day she asked about MCP servers in Slack. Three days of back-and-forth later — with IT asking about the service account and security asking where the credentials would live — Claire had to move on to other work. It was a lost opportunity for productivity improvement and a story all too familiar.
This is happening across every enterprise
Every enterprise is hitting the same wall. Employees need to connect AI assistants to the tools they use every day. The setup process often requires support tickets across multiple teams and ends with credentials scattered across end user devices. Most people either give up or find a way to bypass the policies entirely. In the end shadow AI becomes the direct result of making the safe path the slow path.
So we asked a different question: what if the fastest path was actually the safest one?
What if Claire could just request the access she needed in Claude?
No support tickets.
No new software on her devices.
No sharing of Google credentials over Slack or email.
Full audit trail for security.
Zero manual steps for IT.
What we built
We built that solution. Three things make this different:
First, an identity-aware MCP proxy that governs every tool call in real time. We’ve spent more than 5 years building an industry-leading IGA platform and robust connector ecosystem. That foundation powers a new control layer between AI agents and your enterprise systems. We’re hosting over 3,000 MCP servers in our platform, so virtually any application with an API is available out of the box. Enterprise agents are first-class identities with their own credentials, lifecycle states, and ownership. Service credentials never touch a user’s laptop. They’re vaulted centrally with automatic rotation. Secure by default.
Second, fine-grained policy enforcement on tools and data access. Flexible, dynamic policies define which tools an agent can call directly or with step-up approval, whether it’s working autonomously or alongside a human. Policies automate based on role, department, and context. No manual gatekeeping. No blanket blocks. Governance that scales with adoption instead of against it.
Third, self-service access that’s actually fast. End users request the AI tools they need and get provisioned in seconds through policy-based auto-approval or routed human approval. No tickets. No waiting. No more shadow AI born from frustration.
Here’s a preview:
The use cases span every department: marketing teams getting secure read-only access to analytics tools through their AI assistants. Sales and BDRs prospecting and building accounts plans using AI agents to pull data from Salesforce, Hubspot, and Gong. Developers connecting their coding agents to GitHub without sharing personal access tokens.
Meanwhile, security and IT enabled the business to go fast with AI while keeping the company data secure. And CIOs and CISOs can brag to their boards about AI adoption at the company.
AI Access Management is currently in early preview with select customers.
Today Claire runs the Google Analytics reports in 60 seconds; her days of manually downloading CSV files are behind her. If you want to see what we’ve built, book a demo.
