We check every AI action in your tools — so your people use AI safely, and the audit trail proves it to anyone who asks
Nobody cares about AI safety mid-task — but it is important.
We make the most accessible AI the most secure. Your employees stop looking for AI alternatives.




Security data
Inline, observable, and accountable.
Every prompt passes through the Kvarts gateway on its way to the model. Injection attempts, secrets, personal data, jailbreaks and unsafe output are caught inline — before anything reaches the AI.
Risky content doesn’t just error out — it gets a verdict. Kvarts blocks it, masks the sensitive part, or holds the action for a human yes. Work continues, safely.
Every AI action keeps its full trace — the input, the policy verdict, the latency and who approved it. An audit becomes an export, not a project.
Kvarts runs in Europe and keeps personal data inside your boundary — masked before it leaves, restored only where policy allows.
from openai import OpenAI
client = OpenAI(
base_url="https://gateway.kvarts.ai/v1",
api_key="sk-kvarts-...",
)
response = client.chat.completions.create(
model="anthropic/claude-sonnet-4.5",
messages=[{"role": "user", "content": prompt}],
)
# Compatible with the Kvarts gateway — keep your provider SDK.const result = await fetch("https://api.kvarts.ai/v1/pii/mask", {
method: "POST",
headers: { Authorization: `Bearer ${process.env.KVARTS_API_KEY}` },
body: JSON.stringify({
text: customerMessage,
action: "tokenize",
restore_response: true
})
});
// Protect data with one focused API call.{
"mcpServers": {
"protected-filesystem": {
"command": "kvarts",
"args": ["mcp-proxy", "--", "npx", "-y",
"@modelcontextprotocol/server-filesystem", "/path"]
}
}
}const client = new OpenAI({
apiKey: process.env.KVARTS_API_KEY,
baseURL: "https://gateway.kvarts.ai/v1"
});
await client.chat.completions.create({
model: "gpt-4.1",
messages,
extra_headers: { "X-Kvarts-Cache": "semantic" }
});
// Enable caching without changing client code.Get started.
Start where it makes sense.
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Get immediate access to the system and explore how agents, workflows, and execution fit together. Ideal for teams that want to move fast and stay hands-on.
Not sure which path fits? Most teams don’t know at first — and that’s fine. You can start self-serve and switch later, or talk with us before committing. The system is designed to adapt either way.