Future-proof solution
Why teams switch
One control tower across teams
Unite engineering, product, and data teams in one place. Shared truth, role-based workflows, and human-in-the-loop feedback that drives continuous improvement.
Deploy anywhere, safely
Our cloud, your cloud, or your servers. Private connections supported. Roll out safely and roll back fast.
Compliant, secure and flexible
SOC 2-certified, GDPR-compliant, and aligned with the EU AI Act. Manage risk responsibly with EU or US data residency and regional storage and processing across open and closed ecosystems.
FAQ
Frequently asked questions
What is the difference between Langfuse and Langsmith?
Langfuse and LangSmith are both platforms built to support teams developing LLM-powered applications, but they differ in their origins and focus. Langfuse started as an open-source observability tool, focusing on tracing, logging, and evaluating LLM application performance. LangSmith, built by the creators of LangChain, is more tightly integrated with the LangChain ecosystem and also focuses on observability and evaluation, with additional tooling for prompt and chain management. Both are evolving to support more of the LLM application lifecycle, but observability remains their core strength.
Is Langfuse or Langsmith open source?
Langfuse is available as an open-source project, which makes it appealing for teams that want flexibility and control over their infrastructure. It also offers a managed cloud version for ease of deployment. Langsmith, on the other hand, is a closed-source platform developed by the creators of LangChain and is closely tied to the LangChain ecosystem. For teams that prioritize open tooling, Langfuse may be a better fit. For those looking for a vendor-managed solution with broader lifecycle coverage and cross-platform compatibility, including observability, Orq.ai offers a fully managed platform designed to integrate with a variety of LLM frameworks and workflows.
Can Langfuse or Langsmith handle more than observability?
Yes, both Langfuse and Langsmith are expanding their capabilities beyond observability. Langfuse is introducing features for feedback collection, versioning, and some deployment workflows. Langsmith offers prompt versioning, dataset management, and limited tooling for testing and evaluation workflows. However, neither platform currently offers full support for the end-to-end development lifecycle of LLM applications, such as collaborative design environments, agent orchestration, or production-grade deployment workflows.
Are Langfuse and Langsmith suitable for non-technical users?
Langfuse and Langsmith are primarily built for developers and technical users. Both platforms require familiarity with LLM development, prompt engineering, and application monitoring. Non-technical users may find the interfaces and workflows less accessible without engineering support. For teams looking to include product managers, domain experts, or other non-developers in their GenAI workflows, a platform like Orq.ai may be more suitable.
How does Orq.ai compare to Langfuse and Langsmith?
Orq.ai differs by offering an end-to-end platform purpose-built for the full LLMOps lifecycle. While Langfuse and Langsmith focus primarily on observability and evaluation, Orq.ai includes capabilities for design, deployment, monitoring, and optimization of agentic AI systems. It also provides a collaborative interface that supports both technical and non-technical team members, helping GenAI teams move from prototype to production with greater speed and clarity.
