Apertis AI

AI control plane for coding agents and AI apps, with one governed API path across 30+ model providers.

Overview

Apertis is an AI control plane for coding agents and AI applications. It puts a single governed API path in front of more than thirty model providers, so access, budgets, routing and spend are controlled in one place instead of per integration.

Key features

Multi-provider routing (30+ providers, 500+ models)
Virtual keys for controlled access
Hard budget and quota enforcement
Free prompt caching for repeated contexts
Context compression with cheaper models
Pay-as-you-go fallback after quota exhaustion
Request-level usage attribution and billing
Support for OpenAI-compatible and Anthropic SDKs
Fallback rules and route health management
Regional hosting options (US, EU, UK, AU)

Pros

Drop-in integration—keep existing SDKs, change only base URL
Predictable monthly costs with subscription plans
Comprehensive provider coverage including OpenAI, Anthropic, Google, DeepSeek, Mistral
Free prompt cache reduces repeated-context costs
Hard budget caps prevent runaway agent spend
Works with multiple coding agents without SDK rewrite
Detailed usage records and cost attribution per request
Flexible billing—mix subscription and pay-as-you-go

Cons

Requires custom endpoint support in agent/SDK
Model and route availability depends on provider policy and account configuration
Subscription quotas vary significantly by plan tier
Additional layer adds latency compared to direct provider access

Use this if

You need centralized spend control across multiple AI providers, want to use coding agents with predictable monthly costs, or require budget enforcement and model governance for AI applications.

Skip this if

You only use a single AI provider directly, don't need budget controls, or prefer direct provider APIs without an intermediary layer.

Best for

Coding agents and AI applicationsTeams managing multi-provider AI spendDevelopers using Claude Code, Cursor, or ClineOrganizations needing budget controls and model governanceProjects requiring prompt caching and context compression