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LLM Observability for Developers
Helicone.ai is creating an advanced observability platform tailored for developers working with Large Language Models (LLMs). Our goal is to simplify and enhance the operational side of deploying these models, making it easier for developers to monitor, manage, and optimize their AI applications at scale. Helicone provides a unified view of performance, cost, and user interaction metrics for various LLM providers, like OpenAI, Anthropic, and LangChain, empowering developers to make their LLM deployments more efficient, reliable, and cost-effective. ### Key Features 1. **Centralized Observability**: Our platform captures and visualizes detailed logs and metrics across all LLM deployments. With tools for prompt management, performance tracing, and debugging, Helicone provides real-time insights into the inner workings of your LLMs. 2. **LLM Performance Optimization**: Helicone supports prompt experimentation, success rate tracking, and fine-tuning, allowing you to continuously improve response quality and efficiency. This level of insight makes it easier to deliver high-performing, cost-effective AI applications. 3. **Flexible Data Management**: We understand that data privacy is critical. Helicone supports deployment options for dedicated instances, hybrid cloud integrations, or self-hosted environments, allowing clients to maintain control over their data and ensuring compliance with privacy standards. ### Built for Developers and Data Scientists Helicone is designed to meet the needs of engineers and data scientists who require transparency and control over their LLMs. From chatbots to document processing systems, Helicone equips you with the insights needed to track costs, understand user interactions, and optimize outputs—all from one intuitive platform. By combining observability with LLM-specific insights, Helicone is redefining AI monitoring, empowering developers to deploy and scale their AI models with confidence.
Helicone positions itself as an AI Gateway and LLM Observability platform that helps developers route, debug, and analyze AI applications. It emphasizes observability, monitoring, and reliable AI app delivery with usage-based pricing and scalable plans.
The product provides routing, monitoring, prompts testing, datasets, playground, HQL query language, alerts, reports, caching, rate limit handling, webhooks, gateway functionality, and data retention controls. It supports integration with OpenAI, Anthropic, Azure LiteLLM, Anyscale, Together AI, OpenRouter, and others, enabling users to monitor requests, segments, sessions, users, and performance metrics; includes a pricing tier structure with a calculator and trial periods. Features include monitoring of requests, sessions, user analytics, prompts testing, datasets, prompts scoring, alerts, and a gateway with caching and rate-limit handling to improve AI app reliability.
Who it’s for: Developers and engineering teams building and operating AI applications that rely on LLMs and require observability, debugging, and reliable routing for AI workloads.
Public pricing pages with multiple product tiers, 7-day free trials, and enterprise/custom offerings indicate active go-to-market and growth trajectory; mentions of integrations and a 2025 copyright suggest ongoing traction and product maturation.
Justin is the founder of Helicone, a company dedicated to improving the lives of developers using LLMs. With 5+ years of experience tinkering and hacking on various projects, Justin has honed his technical skills and understands the critical elements of good software infrastructure. Before starting Helicone, Justin was a developer evangelist and teacher at Apple, where he developed a deep passion for supporting developers and their success.
Barak is a co-founder at Helicone. Previously, he was a machine learning engineer at Sisu Data building scalable machine learning workflows for enterprise customers. Before that, he did research at the Stanford AI Lab and was a teaching assistant at Stanford, where he graduated from his MS and BS degrees. In his spare time, Barak bikes around the bay and sits for long hours at coffee shops.
Log requests made to OpenAI and track costs, result quality, and latency with one line of code
Helicone provides an observability and management layer for language-model-powered products. It logs completions, tracks request metadata, offers a one-line-integration proxy, caching, retries, and an analytics interface to monitor costs, latency, and result quality across users, models, and prompts.
From the original launch (Feb 2023) — may be outdated.
Formerly “Prompt Zero”, “TableTalk”, “Valyr” · why startups rename →
Call every LLM API like it's OpenAI [100+ LLMs]
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