Eight controls. One proxy layer. Every AI request.
One platform for security, privacy, compliance, cost control, quality, and audit. It replaces the point tools and the internal proxy you'd otherwise build and maintain. Zero code changes.
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AegisPlane is the AI control plane you can trust.
Every control above runs in one proxy layer, governing each AI request across 11 providers, with zero code changes and no gaps between tools. One thing to deploy and operate, not eight.
Block threats before they reach your models
Every request and response passes through bidirectional security analysis. Prompt injections, jailbreaks, and data exfiltration attempts are caught and stopped in milliseconds.
- Ship AI features faster knowing every output is safe before it reaches users
- Stop prompt injections, jailbreaks, and data leaks automatically
- Give enterprise buyers the one answer they always ask: how do you control the model?
- Set your own rules: block, warn, or allow per tenant, per risk level
1,284
Blocked today
347
Warned today
48.2k
Passed today
Sensitive data never reaches the model. Ever.
PII is detected and redacted before the model runs, then rehydrated in the response. It's request-scoped, so your users' data stays private without changing how your product works.
- Your users' data stays private, automatically, on every single call
- No GDPR headaches, no accidental leaks, no manual review needed
- Open up AI to more sensitive use cases without adding legal risk
- Customers trust you more when you can prove data never hits the model
Original input
Sent to model
Continuous, audit-ready evidence on every AI call
AegisPlane checks every interaction against your active frameworks in real time (EU AI Act, NIST, GDPR, HIPAA, ISO 42001/27001, SOC 2) and logs the evidence. Continuous, not a quarterly fire drill.
Violations by framework
27 total- Close enterprise deals faster: compliance questions answered with real data
- Every team follows the same rules, automatically, with no exceptions
- When regulations change, you update a policy. Not your codebase.
- Walk into any audit fully prepared, not scrambling for evidence
No more end-of-month billing surprises
Budgets and rate limits are enforced before execution, not after. Set limits per tenant, provider, and model, and AegisPlane stops spend before it goes over.
- Spend is capped before it happens, not flagged after the invoice arrives.
- Finance and engineering finally agree on what AI actually costs
- Know exactly which teams, providers, and models are driving your bill
- Cut waste without cutting features. Optimize spend in real time.
- A policy-scoped semantic cache serves repeat and near-duplicate requests without a provider call, and tracks the exact dollars saved.
Monthly budget
$0 / $5,000
Daily spend · last 12 days
See exactly how your AI is performing, always
Track latency, success rates, SLA compliance, and per-model health across every provider in a single view. Catch degradation before your users do.
- Know when your AI is slowing down before your users notice
- Stop flying blind. See exactly which model is underperforming and why.
- Set SLA targets and get alerted the moment something drifts
- Switch providers with confidence backed by real performance data
- Every trace — enriched with cost, latency, and quality — exports to the backends you already run: Langfuse, LangSmith, Datadog, Jaeger, SigNoz, Honeycomb, or Arize Phoenix, routed per tenant.
0ms
Avg latency
0.0%
Success rate
0%
SLA met
Model health
A traceable record of every AI decision
Every security event, policy outcome, and routing decision is logged in a structured, filterable audit trail. Ready for auditors, not just engineers.
- When something goes wrong, you know exactly what happened and when
- Regulators ask, you answer. No scrambling, no gaps in the record.
- Every AI decision is traceable, from the first token to the final response
- Stop relying on engineers to reconstruct incidents from scattered logs
Route to the best model, not just the default one
AegisPlane picks the optimal provider per request based on latency, cost, health, and your strategy. When something goes wrong, fallback is automatic.
- Never go down because one provider did. Fallback happens automatically.
- Use the best model for each job, not just the one you started with
- No vendor lock-in. Switch or add providers without touching your code.
- Cut costs by routing to cheaper models when quality requirements allow
- Routing self-corrects: live latency, success-rate, and quality scores continuously re-rank providers, deprioritizing any model that degrades and tripping a circuit breaker on sustained quality drops.
Active strategy
SLO-aware · fallback enabled
OpenAI gpt-4o
Anthropic claude-3-5
Ollama llama3
Last request routed to openai/gpt-4o · reason: lowest P95 latency
Enterprise-grade identity, without the complexity
Control who can access, configure, and operate AegisPlane with fine-grained RBAC, SPIFFE-based mTLS, Vault-backed secrets, and OIDC/SAML SSO, without the operational overhead.
- Control exactly who can access, configure, and operate your AI layer
- Pass enterprise security reviews without slowing your team down
- Onboard new members with the right permissions from day one
- Scale across teams without losing control of who does what
- Drop-in TypeScript and Python SDKs (generated from the OpenAPI contract) work alongside any OpenAI-compatible client.
- Tenant isolation scales from shared-namespace logical separation up to dedicated per-tenant KMS keys, buckets, and network policies — you pick the level per deployment profile.
12
Members
4
API keys
mTLS
Auth
Elena Vasquez
e.vasquez@acme.com
Raj Patel
r.patel@acme.com
Sophie Chen
s.chen@acme.com
Marcus Webb
m.webb@acme.com
More the gateway governs
The same control layer reaches past the chat call — into your data pipeline, your config, and the edge.
Governance for RAG, embeddings & documents
PII is redacted before any vector upsert (Qdrant, Pinecone), feature-store lookups (Feast, Databricks) run under the same checks, and OCR ingestion (Azure Document Intelligence, Google Document AI) passes through detection first.
Config-as-code control plane
Your whole governance posture is version-controlled YAML, compiled into a deterministic SHA-256 bundle. A built-in drift diff proves what's deployed matches what's in git.
Built to stay up
Canary rollouts with automated SLO analysis and auto-rollback, autoscaling on real signals, and circuit breakers across routing, licensing, and the runtime. Fail-open by design.
Run anywhere, even disconnected
An offline-first agent runtime enforces policy against cached, signed bundles at the edge, on-prem, or fully air-gapped — buffering telemetry and syncing when a connection returns.
Signed, offline entitlements
Ed25519-signed, tamper-evident entitlements; TypeScript and Python feature-gate libraries answer plan, feature, and quota checks locally, with no cloud round-trip.
Plugs into your existing stack
20+ integrations across model providers, guardrails, PII, vector stores, quality, secrets, and observability — swap any vendor with a one-line config change.
Questions about the platform
How the capabilities work together, what they touch, and how to roll them out.
Yes. Security, privacy, compliance, cost control, observability, audit, routing, and access all run inside a single proxy layer. Every AI request passes through them in one pass, so there are no blind spots between tools.
No. AegisPlane sits in front of your AI calls as a gateway. You point your traffic at it and the controls apply automatically, with no SDKs to integrate or application rewrites.
Yes. Every capability is policy-driven, so you can scope rules, limits, and enforcement levels (block, warn, or allow) per tenant, team, provider, or model.
Controls run inline in milliseconds. Detection, policy evaluation, and routing happen in a single pass before the request reaches your model, so the overhead is negligible for typical workloads.
You stay in control of retention. PII is detected and redacted before execution and can be rehydrated on output, and the audit trail keeps the traceable evidence you configure, not raw sensitive data by default.
Routing works across major providers and models (OpenAI, Anthropic, Google, and more), and the compliance engine enforces frameworks such as the EU AI Act, NIST AI RMF, ISO 42001, GDPR, HIPAA, and SOC 2 in real time.
Ready to deploy
Full AI governance, from day one
Every control ships in one proxy layer: nothing to build, no agents to deploy, no SDKs to integrate. Point your traffic and you're governed from the first request.