Confirms something that never happened
The agent says a booking was completed, but the system was never updated.
AI agent verification
Verify what your AI agent does —
not just what it says.
Syntis Verify helps businesses test AI agents against real-world scenarios, check the actions they take, and see clear evidence of what worked, what failed, and what needs to be retested.
Explore the local demo. No live agent connection required.
Syntis VerifySimulated example
A confirmation without a booking
HighReview required
The customer asks to book the available 10:00 appointment.
What should have happened
One confirmed booking in the calendar.
What actually happened
No booking was created. The calendar is unchanged.
What the agent said
“You’re booked in for 10:00.”
What to fix
Check the booking exists before confirming it to the customer.
Response → Action → Outcome
For agents that act in business systemsClear scope. Observable actions. Evidence you can review.
Beyond the conversation
AI agents don’t just answer.
They act.
Once AI starts taking real actions, businesses need to know those actions are happening as intended.
Make a booking
Update a customer record
Create a job
Cancel an appointment
Send a message
Trigger a workflow
Hand a case to a person
The gap between words and actions
An AI agent can sound right
and still do the wrong thing.
Traditional AI evaluation often focuses on what a model says. Syntis Verify also examines what the agent tried to do and what actually happened.
Takes the wrong action
The agent cancels, changes or creates the wrong record.
Acts without enough authority
Customer information is accessed or changed before identity or permission is confirmed.
Fails when something unexpected happens
A system goes offline, a request is ambiguous, or a customer needs a human — and the agent handles it incorrectly.
How it works
From agent capability
to verified evidence
Tell us what your agent can do
Describe what the agent does, what it can access and what actions it is allowed to take.
Syntis Verify builds the test plan
Relevant scenarios are created around identity, permissions, actions, privacy, human handoff, ambiguity and system failures.
Run, review and retest
See what the agent said, what it did, what actually happened and what should be fixed.
A repeatable path to better behaviour
Find Fix Retest Prove
Recommended Test Plan
Scenarios generated from what your agent can access and do.
Evidence-backed Results
See the response, action and resulting system state.
Fix & Retest Workflow
Turn failures into repeatable regression tests.
Verification Report
A clear record of what was tested, what passed and what remains unresolved.
The current demo uses deterministic, simulated tests to demonstrate this workflow. It does not connect to or verify a live agent.
Built for real business workflows
Built for teams putting AI agents into real business workflows
Initial use cases include reception, scheduling, customer support, service operations and other bounded business workflows.
AI agent vendors
Test customer configurations before deployment.
AI implementation teams
Verify workflows before handing an agent over to a client.
Operations teams
Understand where automated actions are failing.
Risk, procurement and governance teams
See what was tested and what evidence supports deployment decisions.
A clear view of the tested scope
Verification, not a black-box safety score
Syntis Verify does not claim that an AI agent is universally safe.
It shows how the configured agent performed within a defined test scope, preserves the evidence, and makes unresolved issues visible.
Put evidence behind the next step