otari provides an open‑source control plane that lets engineering teams route, budget, optimise costs, and secure large language model (LLM) traffic across multiple providers without vendor lock‑in. The platform can be self‑hosted, giving organisations full control over their LLM infrastructure while supporting the models they already use. It also includes approval workflows and document search across connected apps to streamline everyday AI‑driven work.
Funding
Funding not disclosed
Founders
Product
Problem
Engineering teams face fragmented management of large language model (LLM) usage, needing to switch between providers, control costs, enforce security policies, and avoid vendor lock‑in, which complicates scaling AI services in production.
Solution
Otari offers an open‑source control plane that centralizes routing, budgeting, cost optimization, and security for LLM traffic across multiple providers. By providing a single layer of infrastructure, teams can select any compatible model, enforce policy‑driven approvals for AI actions, and maintain full oversight of usage. The platform can be self‑hosted, giving organizations complete control over their AI stack without reliance on a single vendor. Integrated observability and guardrails ensure safe operation, while open‑source libraries support flexible agent orchestration and model evaluation. This enables reliable, scalable deployment of LLMs in production environments while keeping costs predictable and security transparent.
Target Audience
Primary customers are engineering and DevOps teams that build and operate AI‑enabled applications at scale, particularly those requiring multi‑provider LLM management and strict cost or security controls.
Features
- Unified control plane for routing LLM requests to any provider or self‑hosted model
- Policy engine for budgeting, cost optimization, and approval workflows before AI actions execute
- Built‑in security and guardrail libraries (any‑guardrail) for observability and human oversight
- Open‑source libraries (any‑agent, any‑llm) for flexible agent orchestration and model selection
- Self‑hosting capability to eliminate vendor lock‑in and retain full data control
- Compatibility with existing AI workflows and integration with connected applications for document search and augmentation