Every agentcall passesthrough here
Argate sits between your autonomous AI agents and models as an ultra-fast in-memory security layer. PII masking, human approval, and autonomous pentesting — one-line integration.
No credit card required.
Your agents read customer records, carry production keys and can move company money. Nothing sits between them and the model. Argate sits there.
Point your OpenAI-compatible baseURL at Argate. Prompts, tools and code stay exactly as they are.
On-prem, Argate runs inside your VPC, bare-metal or private Kubernetes cluster with no cloud dependency.
Start on Cloud in two minutes; move to single-tenant Private Cloud or fully isolated On-Premises.
Real data never reaches the model.
- 01 · What your agent sentyour network
Prepare a credit-line review for Ayşe Demir (national ID 10293847561). Salary account TR33 0006 1005 1112 3456 7890 12.
- 02 · What the model receivedLLM provider
Prepare a credit-line review for (national ID ). Salary account .
- 03 · What the model returnedLLM provider
Review ready: suggested limit for is $25,000. Repayments will be drawn from .
- 04 · What your user seesrestored in-memory
Review ready: suggested limit for Ayşe Demir is $25,000. Repayments will be drawn from TR33 0006 1005 1112 3456 7890 12.
Anything irreversible waits for a human.
$50,000 vendor disbursement to an external IBAN.
- Agent
- agent-proc-418 · gpt-4o
- Recipient
- TR33 0006 1005 1112 3456 7890 12
- Amount
- $50,000.00
- Reference
- INV #8921-A
- Policy
- ARG-POLICY-FIN-THRESHOLD
- 01Tool call intercepted
- 02Policy matched
- 03Notified #finance-approvals
- 04Human decision
Loops die before they burn your budget.
Database lock loop. Re-fires a heavy SQL aggregation after every timeout.
- 01run_sql(aggregate_q4_revenue)
- 02run_sql(aggregate_q4_revenue)
- 03run_sql(aggregate_q4_revenue)
- 04run_sql(aggregate_q4_revenue)
- 05run_sql(aggregate_q4_revenue)
- 06run_sql(aggregate_q4_revenue)TRIP
- 07run_sql(aggregate_q4_revenue)never sent
- 08run_sql(aggregate_q4_revenue)never sent
- 09run_sql(aggregate_q4_revenue)never sent
- 10run_sql(aggregate_q4_revenue)never sent
Attack your own agents before anyone else does.
OWASP LLM Top 10
enforced at the gateway| Code | Risk | Mitigation | Layer |
|---|---|---|---|
| LLM01 | Prompt Injection & Jailbreak Contextual guardrails + MOCK_RESPONSE rule | Contextual guardrails + MOCK_RESPONSE rule | in-memory guard |
| LLM02 | Sensitive information disclosure DeepGuard Mod 10/11 + Luhn in-memory redaction | DeepGuard Mod 10/11 + Luhn in-memory redaction | pure RAM |
| LLM04 | Model DoS & runaway loops Runaway Circuit Breaker | Runaway Circuit Breaker | auto-trip |
| LLM07 | System prompt extraction Egress heuristic filter & masking | Egress heuristic filter & masking | egress |
| LLM08 | Excessive agency & tool misuse JIT human-in-the-loop webhook gate | JIT human-in-the-loop webhook gate | state hook |
| LLM10 | Unbounded consumption Token bucket & per-agent budget | Token bucket & per-agent budget | token bucket |
The security layer also makes it faster.
Different words, same meaning. The model is never called.
“How do I request a corporate credit line increase?”
“Where can I apply to raise our company card spending limit?”
Send a session ID. Argate carries the history.
- userPrepare a corporate credit application for David Miller.
- agentDraft created for David Miller at $50,000.
- userUpdate his approved limit to $100,000 instead.← only this is sent
Your agent sends only the new message; Argate stitches in the session history. No extra infrastructure on your side.
Your network. Your rules.
Argate sits on a single line between your orchestrator and your inference engine. No change to agent or model code.
On your Kubernetes or bare metal, with zero external egress.
- LangChain
- LangGraph
- CrewAI
- AutoGen
- Semantic Kernel
- LlamaIndex
- 01DeepGuard PII
- 02JIT approval
- 03Circuit breaker
- 04Guardrails · OWASP
- 05Ingress mapper
- vLLM
- Ollama
- TGI
- llama.cpp
- TensorRT-LLM
One
line.
LangChain, CrewAI, AutoGen or your own code — prompts, tools and workflows stay as they are. Only the OpenAI-compatible baseURL changes.
- 01Sign upFree account at app.argate.ai.
- 02Change the URLPoint baseURL at Argate.
- 03You’re coveredPolicies engage automatically.
1from openai import OpenAI2 3client = OpenAI(4- base_url="https://api.openai.com/v1",5+ base_url="https://gateway.argate.ai/v1", # on-prem: http://argate.internal:8080/v16 api_key="sk-argate-live-token",7)8 9response = client.chat.completions.create(10 model="llama-3.3-70b-instruct", # or local vLLM / Ollama11 messages=[{"role": "user", "content": "Inspect customer #491 & transfer funds"}],12)Start at $0.
Scale to air‑gapped.
Plus
POPULAR- —All security engines
- —100 requests / day
- —3 endpoints
- —3 agents
- —10 pentests / month
Pro
For production- —All security engines
- —300 requests / day
- —5 endpoints
- —5 agents
- —25 pentests / month
No credit card required.
Talk to
an engineer.
30-minute technical evaluation and live POC planning.
- 01Air-Gapped security design
- 02GDPR / KVKK compliance review
- 03JIT & Circuit Breaker configuration
24-hour technical response · mutual NDA
30-minute technical session
A live demo against your architecture, and a POC plan.
Frequently asked.
Yes. Argate runs 100% locally in isolated, offline environments. Zero external cloud dependency.
No. Argate operates on a zero-copy in-memory architecture; it adds zero perceptible overhead to LLM response time.
vLLM, Ollama, Llama 3, DeepSeek, Qwen, TGI, and all REST APIs.
No. Just point your baseURL to Argate. Zero code changes.
When an agent calls a high-risk tool, the HTTP session is suspended. An alert is sent to your dashboard or Slack. Once approved, the request continues.