LangSmith Alternatives: What to use if you need more security and control

Key Takeaways

LangSmith alternatives offer diverse solutions, from open-source frameworks to in-depth observability platforms.

Each tool is tailored to specific needs, such as evaluations, user engagement (analytics), or agent testing.

LangWatch.ai stands out as the go to platform for LLM Evaluations and Agent testing.

LangSmith is an advanced tool designed for LLM observability, helping developers monitor and improve the performance of language models. But for all its strengths, recent security incidents have raised new questions: how production-ready is LangSmith really for enterprise deployment?

The June 2025 disclosure of a vulnerability in LangChain’s LangSmith, which allowed malicious actors to access prompt logs and user traces, was a wake-up call. For enterprises handling proprietary logic, sensitive customer data, or operating under compliance mandates like ISO 27001 or SOC 2, security cannot be an afterthought.

The LLM observability and evaluation market is evolving fast, with tools ranging from lightweight open-source frameworks to enterprise-grade platforms. While each solution has its strengths—be it tracing, analytics, or model monitoring—the most forward-looking teams are seeking more than just logs and dashboards.

They need a platform that can:

• Evaluate and debug LLM behavior at scale

• Simulate complex, multi-agent workflows before production

• Integrate with any stack without vendor lock-in

• Meet enterprise security and compliance requirements

In this guide, we’ll explore the top 6 LangSmith alternatives in 2025, offering insights into their key features, pros, and how they compare in terms of evaluation metrics, performance, and agent simulations. If you're considering a switch from LangSmith or exploring other options for your LLM needs, read on to discover the best alternatives available.

Why look beyond LangSmith?

LangSmith is great for experimentation and evaluation of LangChain-based pipelines, but it comes with trade-offs:

• ❌ Security Gaps – Until recently, LangSmith lacked common security features like audit logging, RBAC, or encryption controls.

• ❌ Vendor Lock-In – LangSmith is tightly coupled to LangChain and hosted exclusively by LangChain, which raises concerns for teams wanting more deployment flexibility.

• ❌ Limited Support for Multi-thread conversations/ multi-model Agents – Complex agent systems built on without or with a framework like CrewAI, DSPy, OpenAI Assistants, or even custom frameworks are only partially supported.

For highly regulated industries, like finance, healthcare, or AI-native SaaS platforms, these trade-offs can create unacceptable risk. That’s why a new generation of tools is emerging to offer deeper control, stronger security, and broader integration.

The best LangSmith alternatives

Let’s break down the top players building alternatives to LangSmith today.

1. LangWatch.ai - LLM Observability, Evaluations, Agent simulations & Collaboration

LangWatch is the secure, enterprise-ready alternative to LangSmith, purpose-built for teams who demand both deep evaluation capabilities and advanced agent testing. Designed from the ground up for complex Agentic systems, LangWatch delivers observability, automated optimization, and enterprise-grade security without locking you into a single framework.

• Framework-Agnostic Integration – Works seamlessly with OpenAI, Anthropic, CrewAI, AutoGen, DSPy, and custom-built agent frameworks via standardized API integration—no ecosystem lock-in.

• Proactive Agent Simulation – Test multi-turn conversations, complex workflows, and tool-usage patterns that go far beyond simple input/output checks. Perfect for validating the reliability of customer support bots, compliance agents, or multi-agent orchestration before production deployment.

• Collaboration and UI friendly – A dual interface lets domain experts work through the LangWatch platform UI while developers access programmatic APIs for automation, CI/CD pipelines, and large-scale experiments.

• Automated Prompt Optimization – Direct DSPy integration enables machine-learning-driven prompt refinement, generating better-performing variations through structured experimentation.

LangWatch not only solves today’s LLM observability challenges but also future-proofs your AI stack with tools built for regulated, mission-critical deployments.

2. LangFuse – Open-source

LangFuse is a popular open-source observability tools for LLM pipelines. It’s self-hostable indepth tracing, prompt playgrounds, and data tagging.

• ✅ Works well with LangChain, LlamaIndex, OpenAI Functions, and Flowise

• ✅ Strong community and frequent updates

• ⚠️ Lacks Agentic AI systems testing, such as agent simulations

• ⚠️ UI for developers, not made for collaboration

• ⚠️ Lacks enterprise security features out-of-the-box (RBAC, PII redaction, audit logs)

• ⚠️ Some evaluation features are still maturing compared to closed-source SaaS offerings

Best for: Startups and mid-sized teams who want observability + basic evals without vendor lock-in.

3. Phoenix – LLM Monitoring

Phoenix is an open-source tool with a strong focus on model performance monitoring. It supports LLM use cases with features like embeddings visualizations, drift detection, and prompt evaluations.

• ✅ Great for ML Ops teams already using Arize

• ✅ Drift detection and embeddings monitoring

• ⚠️ Focus more on MLops than LLMops

• ⚠️ Lacks full pipeline tracing or agent support

• ⚠️ Requires significant setup and infrastructure knowledge

Best for: MLOps teams expanding into LLMs who need drift monitoring and visibility over vector stores.

Final thoughts: Choosing the right LangSmith alternative

The right platform depends on your priorities whether that’s open-source flexibility, advanced observability, or future-proof agent testing. But if you need a secure, enterprise-grade solution with agent simulation, multi-framework support, and automated prompt optimization, LangWatch leads the way.

Don’t wait until your next production incident to discover the gaps in your LLM pipeline. Start testing smarter, simulating earlier, and shipping more reliable AI products with LangWatch.

👉 Book a demo or start your free trial today.