Payment details slip into chat
Someone pastes a ticket or email into your AI helper. Card numbers and account talk can ride along without anyone noticing.
Caught? Often by luck — or too late.
Control your AI in production
No bugs. No surprise bills. No bad answers. No leaks.
Stop sensitive data from leaking to your AI. We check every message before your AI answers.
One-click packs — pick what fits you
Finance & payments
Card numbers, account details, payment talk
Patient and medical info
Records, appointments, and health-related wording
EU / GDPR data
Personal names, addresses, and sensitive categories
Schools & assistants
Student IDs and internal chat patterns
High-risk prompt guard
Catches risky prompts, even when they look innocent
Knowledge bases & chatbots
Structured FAQs, docs, and customer-facing bots
Used by teams who need to ship AI fast — without breaking trust.
Why teams pick this up now
Then the messy stories start — the kind you only hear about after customers, finance, or legal get involved.
Someone pastes a ticket or email into your AI helper. Card numbers and account talk can ride along without anyone noticing.
Caught? Often by luck — or too late.
A loop, a bad integration, or a busy weekend can rack up usage while your team is offline — then finance asks what happened.
Caught? When the invoice lands.
Your AI tells a customer “free shipping,” a policy exception, or a made-up fact — sounding sure of itself the whole time.
Caught? When someone complains.
Quantlix catches problems like these before your AI answers — so the risky stuff never makes it into what customers see.
Social proof
A perspective from an engineering leader who has shipped platform and security products at global scale.
He’s describing the layer that checks AI traffic before your model answers — and saying it belongs next to the other tools your team already trusts in production.
“They're going after that control layer. This belongs in the toolbox.”
Inayathulla Khan Lavani
Engineering Leader
Former teams at
Built for teams that need real control over their live AI features — wherever you are.
Available now
Your first piece of Quantlix
Quantlix is the platform. Boundary is the product most teams start with — the safety checkpoint that catches risky messages before your AI sees them, with traces and policy outcomes you can show security and compliance.
Plus a dashboard to set the rules — and see what happened.
The Control Plane is where you set things up — deployments, policies, providers, evals, and observability.
The Runtime Layer is the single layer every request passes through — before it reaches your AI, your tools, or your knowledge.
Quantlix Control Plane
Configure & inspect
Where you set the rules
Dashboard, CLI, and API for deployments, policies, providers, evals, observability, and audit logs.
Your application
Your app & APIs
What your customers use
Chat, copilots, agents, and internal tools — the experiences people touch every day.
Quantlix Runtime Layer
BoundaryProduct name for this checkpoint today
In the request path
The safety checkpoint
Every request flows through here before it reaches a model, tool, or knowledge source.
runtime-layer: routes requests, enforces policy, emits traces
Models · Tools · Knowledge
The destinations
Where your AI and tools plug in
AI models, external tools, and your knowledge — swap or route between them anytime without changing your app.
Includes your usual HTTP APIs and MCP (Model Context Protocol) tool connectors when you set them up.
Sideways = each request's path through your app, Quantlix, then your AI and tools. Up and down = how the control plane configures and watches the runtime layer.
That safety checkpoint has a name: Quantlix Boundary — the first product you can use today.
See Boundary →Quantlix grows with you — from your first free test to company-wide rollout.
Connect your app once, then add stricter checks, more teams, and clearer history whenever you need it.
Without rebuilding what already works.
See plans & pricing — whenever you want to compare tiers.
Start free — add a plan when you need more.For teams who ship AI features their customers actually use.