Stop it before it becomes an incident.
A capability of the Axonyx platform. See what is included in Core and Enterprise →
Check every question and answer, stop the risky ones, and keep sensitive data where it belongs.
AI moves in real time. A policy document and a monthly report do not.
Runtime AI security that checks prompts and responses in flight, stopping prompt injection and data loss before they land rather than reporting them after.
Axonyx checks each request as it happens, stops the ones that break your rules, and keeps the proof.
Book a demoCheck every question and every answer
Questions are checked before they reach the AI. Answers are checked before they reach your people. Leaked data, broken rules, attempts to trick the AI and made-up answers are all caught on the way through.
- Checked on the way out and on the way back
- Every request scanned, matched to your rules and scored
- Every check kept as evidence
Keep sensitive data inside the business
People paste customer data, passwords, source code and medical records into AI without thinking. Axonyx catches it first, then lets it through, hides the sensitive part, blocks it, or sends it for approval.
- Spots customer data, passwords, source code and regulated records
- Hide it, block it, or send it for approval
- Works everywhere your people use AI
Catch answers that are confidently wrong
AI is happy to make things up. Axonyx spots claims it cannot back up, then flags them, fixes them, blocks them or asks a human.
- Warns when the AI is guessing
- Flag it, fix it, block it or send it to a person
- Keeps a human in the loop where it matters
Rein in AI agents before they act
Agents move data and set off processes on their own, without anyone watching. Axonyx limits what they can touch, demands sign-off for anything serious, and records every step.
- Limits on what each agent can reach and do
- Sign-off required for anything that matters
- A full trail of everything the agent did
Reach the AI your staff actually use
Most AI use is not in the tools you approved. It is in browser plug-ins, copilots and features quietly switched on inside software you already pay for. Axonyx reaches those too.
- Browser AI, copilots and built-in AI features
- Spots unapproved tools and applies your rules there
- Stops sensitive data before it leaves the browser
Route AI work to the right model
Not everything should go to the same AI. Keep regulated work in your own country, pick the cheaper model where it will do, and switch automatically when a provider goes down.
- Routes by risk, cost and where the data must stay
- Private models for regulated work
- Switches automatically when a provider goes down
Questions we get about real-time AI control
What is runtime AI security?
Runtime AI security checks AI requests and responses while they are in flight, rather than reviewing them after the fact. The check sits between your people or applications and the model, so an unsafe request never reaches the model and an unsafe answer never reaches the person.
Monitoring tools tell you an incident happened. Runtime control means it did not.
How do you stop prompt injection?
Prompt injection is an attempt to smuggle instructions into a model through content it reads, so that it ignores the rules it was given. It can arrive in a pasted document, a web page an agent fetches, or a support ticket.
Axonyx inspects the full request, including retrieved content, before the model sees it. Requests carrying instruction-shaped content are blocked or sent for approval, and the attempt is recorded so your security team can see who was targeted and how.
Can it stop sensitive data leaving the business?
Yes. Requests are checked for the things you have said must not leave: customer records, card numbers, health data, source code, anything you define.
You choose what happens when one is found. Block it, strip the sensitive part and let the rest through, or route it to a model that is allowed to see it.
What happens if Axonyx is unavailable?
You decide in advance. Fail closed means requests stop when the check cannot run, which is what regulated teams normally choose. Fail open means requests continue unchecked and are flagged for review.
The choice is yours to make per environment, so a production banking workload and an internal sandbox do not have to be treated the same way.
Will it slow down our applications?
Checks run in line with the request rather than as a separate round trip, so the added time is small next to how long a model takes to answer.
The honest answer is that it depends on your policies. A simple block list is faster than full content inspection on a large document. We would rather size that against your real traffic in a trial than quote a number that flatters us.
Move from AI chaos
to AI control.
See what your AI is doing, stop what it should not, and keep the proof.
Book a demo