Auriko AI

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Auriko AI
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What is Auriko AI?

Auriko AI is a comprehensive AI control plane designed to manage and optimize LLM inference from prototype to production. It integrates a model gateway, intelligent routing, observability, and FinOps into a single platform, enabling seamless access to multiple model providers through one unified API. The platform supports an OpenAI-compatible drop-in, preserving provider-specific features while simplifying integration.

Key features include intelligent routing that goes beyond headline pricing by modeling workload interactions with each provider's pricing and prompt-caching mechanics, ensuring cost-optimized routing for every request. Real-time signals on provider performance, health, cache behavior, and usage patterns drive optimization, while a quantitative data engine enables cost-optimized routing, cache-cost modeling, and performance tuning. Users can leverage built-in defaults or define custom routing strategies to optimize for cost, latency, throughput, or other objectives.

Auriko routes traffic through a globally distributed edge network with state-of-the-art latency optimization, ensuring continuous uptime with built-in redundancy. It offers flexible key management with BYOK, platform keys, or a combination, and maximizes key utilization through an orchestration engine. Capacity awareness across providers and keys, along with access to a global capacity reserve, ensures on-demand capacity. Spending limits and alerts can be set at workspace or API key level for effective cost control.

Use cases span from startups to enterprises needing efficient, scalable LLM inference. Technical details include a single API for all providers, real-time observability, and quantitative data engine for routing decisions. Auriko is ideal for teams seeking to reduce costs, improve latency, and maintain high availability without complex infrastructure management. With minimal code changes, it accelerates deployment and optimizes inference operations.

Who is it for?

AI engineers, ML engineers, DevOps teams, platform engineers, FinOps teams, product teams

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