LLM Management and Observability Platform: Helicone

LLM Management from a Single Hub

Designed for teams building AI-based products, Helicone serves as an open-source gateway and observability platform. The Y Combinator-backed startup enables large language models (LLMs) spread across different providers to be managed from a single hub. The platform aims to let developers focus on the product instead of spending time on integration processes.

Technical Infrastructure and Integration

Helicone AI Gateway offers an interface compatible with the OpenAI SDK, allowing developers to preserve their existing codebases. Users can switch between more than 100 models such as GPT-4o, Claude, Gemini, DeepSeek, Mistral, and Groq by changing only the model name. Thanks to its Rust-based infrastructure, the platform can process millions of requests with low latency, making it easier to select the most suitable model for speed and cost optimization.

Observability Capabilities

One of the platform’s standout features is its detailed observability layer. While every LLM request made is automatically logged, cost, latency, token usage, and error rates can be tracked on a per-request basis. The technical features offered by Helicone are as follows:

• HQL (Helicone Query Language): Detailed filtering and data querying capability.
• Performance Monitoring: Visualization of multi-step agent flows and error detection.
• Alert Mechanisms: Automatic notifications for abuse and performance issues.
• Price Comparison: Cost analysis tools for more than 300 models and providers.

Deployment and Licensing

Helicone, which is fully open source, is published on GitHub under the Apache license. Companies can use the platform as a cloud service or run it on their own infrastructure (self-hosted) with ready Helm chart options. On the pricing side, alongside a free starter package for individual developers, Pro and Enterprise solutions are offered for scaling teams.