why team AI rollouts break down
Getting AI to your team is easy. Knowing what it's doing is not.
Most teams using Claude Desktop or Claude Code are running it the same way: each engineer sets up their own MCP servers, manages their own credentials, and connects to whatever tools they need. It doesn’t scale.
That’s why 492 MCP servers are exposed to the internet with zero authentication and 97% of AI-related breaches occur at organizations without proper access controls.
There's no audit trail for tool calls
Claude Desktop and Claude Code don't produce a queryable audit log of what tools were called, what arguments were passed, or which user made the call. When a security review asks what your AI did last week, there's no record to pull.
Tool access is all-or-nothing
Native MCP gives a user everything a server exposes or nothing. There's no way to give an engineer read access to Notion while giving a lead write access. Everyone who connects gets the same permissions.
Credentials live on individual machines
Every engineer maintains their own MCP configuration, with their own tokens and server connections. There's no central place to rotate credentials, audit what's connected, or enforce which tools are approved for team use.
Agents use their creator's credentials
An agent running on an engineer's session uses that engineer's credentials and grants. Its tool calls look like the engineer's calls in any log you have. As agent use scales, attribution disappears.
how aptible works
One gateway for your whole team, with controls that actually enforce
Built for teams that have adopted AI tools and want to govern them
Join the waitlist
Your security team wants to know what MCP servers are connected to Claude across the org
Instead of asking engineers to self-report, the gateway maintains the registry. Anything not explicitly approved doesn't get a connection. You control what's reachable before someone connects to something they shouldn't.
Your Snowflake server is connected to your AI tools, but not everyone should have the same access
Engineers get read access. Leads get write access. The analyst team gets no access at all. Define it once at the role level; the gateway enforces it on every tool call.
Answer customer security questionnaires with actual evidence
Customer security reviews now include AI sections. Pull audit records for LLM usage and agent tool calls directly from the platform, without a reconstruction effort.
You're rolling out Claude to 30 engineers and don't want 30 different configurations
Connect your approved MCP servers once at the org level. Push Claude Desktop and Claude Code configurations via MDM so every engineer gets the right setup on day one, with no manual config required.
A customer asks what AI tools touched their data last quarter
Pull a filtered audit record of every tool call, by user and date range, in under a minute. No piecing together logs from individual machines.
An automated onboarding agent is running in production and something goes wrong
Because the agent has its own robot user identity, you can pull every tool call it made, see exactly what arguments it passed, and trace the issue without it being mixed in with your engineers' activity.
