Control, secure, and observe every enterprise AI request.
Infralo sits between microservices and upstream model providers. Virtualize API keys, enforce runtime pre/post guardrails, load balance with sub-4ms cache hits, and capture complete multi-span latency traces.
Control Plane
Four foundational pillars for production AI infrastructure.
Infralo decouples provider credentials from client code, intercepts requests at runtime with custom security hooks, routes traffic across dynamic fallback clusters, and records full-fidelity telemetry.
Virtual API Keys & Secret Virtualization
Store upstream provider keys securely in encrypted enterprise vaults. Issue scoped Virtual API Keys to microservices with hard token limits, model whitelists, rate limits (RPM), and cost ceilings.
Pre & Post Pipeline Runtime Modules
Execute low-latency interceptor hooks before and after LLM inference. Redact customer PII, sanitize prompt injections, enforce schema validation, and route through human-in-the-loop approvals.
Smart Mesh Routing & Sub-4ms Cache
Eliminate provider downtime. Infralo detects upstream 5xx errors or latency spikes in milliseconds and automatically reroutes requests to hot backup providers (OpenAI → Anthropic → Gemini).
Multi-Span Tracing & Cost Attribution
Complete visibility into every LLM request. Inspect multi-span latency breakdowns, prompt/completion token usage, cache hit ratios, and attribute exact dollar spend down to individual engineering teams.
A single line of configuration. Zero SDK lock-in.
Infralo is wire-compatible with the standard OpenAI API specification. Keep your existing client libraries and LangChain agents—just update your base_url to Infralo Control Plane.
# 100% Drop-in with standard OpenAI Python client
from openai import OpenAI
client = OpenAI(
# Point to your Infralo AI Control Plane gateway
base_url="https://api.infralo.com/v1",
# Authenticate with your scoped Virtual API Key
api_key="inf_live_938a0f92b7c1"
)
# Executes runtime guardrails, failover routing, and telemetry automatically
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Analyze quarterly metrics."}]
)
print(response.choices[0].message.content)
Direct vendor sprawl vs. central control plane.
Why leading enterprise engineering teams transition from unmonitored direct API keys to Infralo.
Scattered credentials & blind execution
Microservices embed raw vendor master keys directly in environment variables. When a provider suffers a 503 outage or rate-limit spike, downstream applications crash immediately.
- ✕ Secret sprawl across microservice repos with zero revoke audit
- ✕ Raw customer PII dispatched unredacted to external AI vendors
- ✕ Complete application downtime during upstream provider outages
- ✕ Zero unified cost visibility or per-team budget enforcement
Centralized governance & resilient routing
Master credentials remain locked in your KMS. Applications receive fine-grained Virtual Keys with automated pre/post pipeline guardrails, sub-4ms cache hits, and automatic failovers.
- ✓ Zero master keys in application code; 1-click key revocation
- ✓ In-flight PII redaction and prompt injection sanitization
- ✓ Sub-4ms automated failover mesh across OpenAI, Anthropic, Gemini
- ✓ Multi-span latency waterfalls and exact token spend telemetry
Built for enterprise compliance and private VPC deployment.
Infralo is architected with strict Zero Data Retention (ZDR) and runs either as a managed multi-region control plane or fully self-hosted inside your Kubernetes cluster.
Self-Hosted & VPC Native
Deploy Infralo as a private Helm chart on AWS EKS, GCP GKE, or bare-metal Kubernetes. Sensitive prompts never leave your corporate perimeter.
Zero Data Retention (ZDR)
Prompts and responses are processed in memory and never persisted to disk unless explicit audit logging is enabled by your security administrator.
AES-256-GCM & CMEK
All credentials and metadata are encrypted with customer-managed encryption keys (CMEK) via AWS KMS, GCP Cloud KMS, or HashiCorp Vault.
Technical specifications & architecture details.
Everything you need to know about integrating Infralo into your engineering stack.
/v1/chat/completions, /v1/responses, /v1/embeddings). You do not need to replace your SDK or rewrite agent logic; simply configure base_url="https://api.infralo.com/v1" and pass your Infralo Virtual Key.
Ready to take control of your enterprise AI infrastructure?
Schedule a technical architecture review with an Infralo solutions engineer, or explore our documentation to test a self-hosted cluster in minutes.