A LangSmith Alternative that Takes LLM Observability to the Next Level

Lina Lam· Mar 27, 2025

Both Helicone and LangSmith are capable, powerful DevOps platforms used by enterprises and developers to develop, deploy, and monitor their LLM applications and gain full visibility into their development.

But which platform is better for production? Let's compare.

What Makes Helicone Different?

1. Helicone is Open-Source

Helicone is fully open-source and free to start. Companies can also self-host Helicone within their infrastructure. This ensures that you have full control over the application, flexibility, and customization tailored to specific business needs.

2. Ease of Integration

Developers often choose Helicone for our simple proxy setup. Simply by changing the base URL, you can start logging everything with any providers.

https://oai.helicone.ai/v1 # new baseURL
https://api.openai.com/v1 # old baseURL

Being a proxy, Helicone offers caching, prompt threat detection, key vault, rate limiting, and other useful gateway features.

However, if you don't want to place Helicone in your critical path, you can use our async logging method.

3. Scalable Usage-Based Pricing

Helicone is more cost-effective than LangSmith for two reasons.

First, we operate on a volumetric pricing model that gets cheaper the more requests you have. Second, our paid tier starts at $20/seat/month, which gets you access to all features in Helicone, compared to $39/seat/month for LangSmith. Our seat-based pricing caps at $200/mo for fast-growing teams needing unlimited seats.

Here's how the pricing scales between Helicone and LangSmith:

Comparing Helicone and LangSmith

As a platform that focuses on optimizing your entire LLM lifecycle, Helicone isn't just a great alternative to LangSmith. It also outperforms in scalability and reliability compared to tools like Langfuse and Portkey.

LLM Observability and Monitoring

Security, Compliance, Privacy

Self-Hosting and Deployment Options

UI Comparison: Helicone vs LangSmith

We believe that observability should be simple and intuitive at Helicone, that's why we designed our platform to be easy to use and understand. It's reflected in both our UI and workflow that are designed to make you more productive as a developer.

What's great is that you don't need to be a data analyst to understand the dashboard. It's designed for a wide range of technical experiences.

Integration Example

Helicone's proxy integration requires minimal code changes. Here's an example of integration with OpenAI:

import OpenAI from "openai";

const openai = new OpenAI({
  apiKey: OPENAI_API_KEY,
  baseURL: "https://oai.helicone.ai/v1",
  defaultHeaders: { "Helicone-Auth": `Bearer ${HELICONE_API_KEY}` }
});

See docs for Anthropic, Gemini and more.

LangSmith Dashboard

LangSmith specializes in tracing complex AI workflows, particularly those built with LangChain (built by the same team). LangSmith organizes everything into:

• Runs: Individual operations (like a single LLM call)
• Threads: Groups of related operations that fulfill a user request
• Projects: Collections of traces for different parts of your application

LangSmith's interface is more technical than Helicone's but provides somewhat deeper visibility into complex workflows.

Integration Approach

LangSmith uses an async SDK-based approach. This involves using function decorators to trace your code. For example:

from langsmith import traceable

@traceable
def process_query(question):
    # Application logic
    return response

This method requires more code changes and is more technical but gives you detailed insights into each function.

Which platform should you choose?

We hear our customers say that their experience of monitoring LLM application in Helicone is intuitive and integrates well into any LLM observability tech stack. LangSmith is a great tool, and there are some things we would recommend them over Helicone for, such as if you're an enterprise that is in the LangChain ecosystem.

We've distilled the key features of Helicone and LangSmith into a table to help you decide which platform is best for your needs:

We recommend trying out both platforms to see which one is better for you. If you have any questions, please don't hesitate to reach out!

You might be interested in

• Quick Start with Helicone (Docs)

• Comparing Langfuse vs Helicone

• Comparing Portkey vs Helicone