Least privilege
Per agent, per task
Each agent’s access is learned from real runs and approved by your team before it is enforced.
Exposure report. Held against used, for each agent, after the two-week pilot.
AI-Native Startups & B2B SaaS
When you sell to larger companies, their security review asks what your AI agents can access and how you would know if one misbehaved. “We trust the model” does not pass that review.
The Questions
These are the questions that come up when an AI feature reaches a larger customer.
01
They want a list for each agent, not for each API key.
02
Prompt injection through a customer’s own document is the case they have in mind.
03
A record of each decision, with its reason, that cannot be quietly edited.
04
A named person, not a deploy script.
What You Get
Each answer comes from the gateway itself, not from a policy document.
Least privilege
Each agent’s access is learned from real runs and approved by your team before it is enforced.
Exposure report. Held against used, for each agent, after the two-week pilot.
Evidence
Every decision, with its reason, in a hash-chained ledger that reports any edit.
Coming next: evidence export for auditors.
Control
Calls outside the policy pause for a person. One kill switch stops every agent.
Fit
Early access works best for teams with agents in production or close to it.
A good fit if
Not a fit yet if
Questions
The pilot runs for two weeks in shadow mode. At the end you have an exposure report for each agent: the access it holds against the access it used.
No. StartiQOS is self-hosted, and its traces record the shape of each request, not the values.
Each check takes under 0.05 ms at the 99th percentile in our tests, far less than the model call itself.
Pricing is not published. Book a demo or write to info@startiqosai.com, and the team will share terms for your situation.
Two weeks of shadow mode gives you an exposure report for every agent, with nothing blocked while it learns.