Anthropic acquires Humanloop. Your alternative is Weights & Biases.
Humanloop is shutting down. Meet your alternative: Weights & Biases. Discover how to seamlessly migrate your LLM workflows for tracking, evaluation, and monitoring.
Created on August 14|Last edited on August 18
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Humanloop, a pioneer in AI development platforms, is sunsetting its services following an acquisition by Anthropic. This transition means that after September 8, 2025, Humanloop’s platform and API will no longer be available to users. For many developers and companies who relied on Humanloop’s tools for managing large language model applications, this change marks a significant shift in their workflows. In light of Humanloop’s sunsetting, it’s important to explore strong Humanloop alternative platforms that can fill the gap and support continuous AI development.
In this article, we discuss why Humanloop joined Anthropic and how the company is handling the transition for its customers. We then explore the contributions Humanloop made to the AI industry and highlight Weights & Biases as a powerful alternative that can help AI developers and organizations adapt smoothly to Humanloop’s closure and continue building reliable LLM-powered applications.
Why Humanloop joined Anthropic
Humanloop’s decision to join Anthropic was driven by a shared mission of advancing AI safety and reliability. Anthropic, known as a “safety-first” AI company, focuses on building beneficial AI systems with robust guardrails. By bringing Humanloop’s team and expertise on board, Anthropic aims to strengthen its enterprise AI tools and evaluation strategies. Humanloop’s platform specialized in prompt management, LLM evaluation, and observability, which aligns well with Anthropic’s emphasis on creating AI systems that are safe and perform consistently.
For Humanloop, joining Anthropic offered an opportunity to accelerate the adoption of its ideas on a larger stage. Anthropic is rapidly growing in the enterprise AI space and leads in developing agentic and coding AI capabilities. By integrating with Anthropic, Humanloop’s team can contribute to setting new standards in AI model management and evaluation at scale.
Ensuring a smooth transition for Humanloop customers
Sunsetting a platform as critical as Humanloop could be disruptive, so the team has taken steps to ensure a smooth transition for customers. Humanloop communicated the shutdown well in advance (notification went out by July 2025) and committed to supporting users through the transition period.
To help users migrate off the platform, Humanloop provided tooling and guidance for exporting all data, including prompts, logs, and other resources, via existing API endpoints. For organizations with very large datasets, the team even offered tailored export solutions. Shortly after the shutdown date, all customer data will be removed from their servers to maintain privacy.
Humanloop has also worked with the AI community to point customers toward other solutions, ensuring they can continue their AI projects with minimal downtime.
Humanloop’s contributions to the AI industry
Before its acquisition, Humanloop made a number of important contributions to the AI industry, particularly in the emerging field of LLM operations (LLMOps). Founded in 2020 as a University College London spinout, Humanloop was among the first development platforms for large language model applications.
One of Humanloop’s key impacts was helping to define industry best practices for prompt management, evaluation, and observability. The platform introduced systematic prompt versioning, rigorous performance tracking, human feedback integration, and usage monitoring; capabilities that have since become standard practice in LLMOps. Even as Humanloop sunsets, its innovations will live on through the work of its team at Anthropic and in other platforms that have adopted similar principles.
Weights & Biases as the leading Humanloop alternative
Weights & Biases is a comprehensive AI development platform that not only covers many of Humanloop’s core capabilities but extends them into a full machine learning lifecycle environment. For AI teams looking to iterate quickly on prompts and models, Weights & Biases offers an end-to-end solution through tools like W&B Weave, W&B Models and W&B Inference powered by CoreWeave.
Key strengths of Weights & Biases:
- End-to-end experiment tracking: Log and compare prompt versions, model parameters, outputs, and performance metrics in one dashboard.
- Weave for LLMOps: Includes Traces for debugging multi-step LLM workflows, Evaluations for systematic output scoring, and a Playground for rapid prompt iteration.
- Agents & Guardrails: Track autonomous agent behavior and set safety rules to block undesirable outputs.
- Collaboration & organization: Centralized project spaces with commenting, tagging, dashboards, and reproducible runs.
- Broader ML lifecycle support: Beyond prompts, W&B handles model training, hyperparameter sweeps, model registry, and dataset versioning.
- Easy integration: Works with popular LLM frameworks like OpenAI API, LangChain, and Hugging Face with minimal code changes.
- Reliability & support: A proven platform trusted by leading AI teams, with extensive documentation and enterprise options.
Conclusion
Humanloop’s sunsetting marks the end of one of the first dedicated LLM application platforms. But its departure is also an opportunity for teams to upgrade their workflows. Weights & Biases stands out as the single most comprehensive and future-proof alternative—covering prompt management, evaluation, monitoring, and the entire ML lifecycle in one unified platform.
By migrating to W&B, developers can maintain continuity, enhance collaboration, and accelerate experimentation, ensuring their AI projects remain cutting-edge long after Humanloop goes offline.
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