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MONITOR, EVALUATE & IMPROVE
YOUR LLM APPS


LANGTRACE IS AN OPEN-SOURCE OBSERVABILITY TOOL THAT COLLECTS AND ANALYZES TRACES
AND METRICS TO HELP YOU IMPROVE YOUR LLM APPS.

Start for FreeBook a Demo




ADVANCED SECURITY

LANGTRACE ENSURES THE HIGHEST LEVEL OF SECURITY. OUR CLOUD PLATFORM IS SOC 2
TYPE II CERTIFIED, ENSURING TOP-TIER PROTECTION FOR YOUR DATA.


SOC 2


TYPE II


CERTIFIED


TRUSTED AND RECOGNIZED BY


SEARCHSTAX




PULSE ENERGY


SIMPLE NON-INTRUSIVE SETUP

ACCESS THE LANGTRACE SDK WITH 2 LINES OF CODE

PythonTypeScript
from langtrace_python_sdk import langtrace

langtrace.init(api_key=<your_api_key>)
Read docs


SUPPORTS POPULAR LLMS, FRAMEWORKS AND VECTOR DATABASES

OpenAI

Google Gemini

Anthropic

Perplexity

Groq

Langchain

LlamaIndex

See All


WHY LANGTRACE?


OPEN-SOURCE & SECURE

Langtrace can be self-hosted and supports OpenTelemetry standard traces, which
can be ingested by any observability tool of your choice, resulting in no vendor
lock-in.


END-TO-END OBSERVABILITY

Get visibility and insights into your entire ML pipeline, whether it is a RAG or
a fine-tuned model with traces and logs that cut across framework, vectorDB and
LLM requests.


ESTABLISH A FEEDBACK LOOP

Annotate and create golden datasets with traced LLM interactions, and use them
to continuously test and enhance your AI applications. Langtrace includes
built-in heuristic, statistical, and model-based evaluations to support this
process.


BUILD AND DEPLOY WITH CONFIDENCE


TRACE

TRACE REQUESTS, DETECT BOTTLENECKS, AND OPTIMIZE PERFORMANCE WITH TRACES.


ANNOTATE

ANNOTATE AND MANUALLY EVALUATE THE LLM REQUESTS, AND CREATE GOLDEN DATASETS.


EVALUATE

RUN LLM BASED AUTOMATED EVALUATIONS TO TRACK PERFORMANCE OVERTIME.


PLAYGROUND

COMPARE THE PERFORMANCE OF YOUR PROMPTS ACROSS DIFFERENT MODELS.


METRICS

TRACK COST AND LATENCY AT PROJECT, MODEL AND USER LEVELS.


WHAT OUR CUSTOMERS SAY

Don't just listen to us, hear from current users

Langtrace are not just a genai adoption story, but also a story that a humble,
persistent opensource community can coexist in a highly competitive, emerging
space.

ADRIAN COLE

Principal Engineer, Elastic

It was a very easy, quick integration. Kudos to you guys for that. It doesn't
take a lot of time. That was a fun thing.

AMAN PURWAR

Founding Engineer, Fulcrum

We looked around for observability platform for our DSPy based application but
we could not find anything that would be easy to setup and intuitive. Until I
stumbled upon Langtrace. It already helped us to solve a few bugs.

DENIS ERGASHBAEV

CTO, Salomatic


LATEST FROM LANGTRACE

Sending Traces from Langtrace to New Relic: A Step-by-Step Guide

Discover how to enhance your LLM application monitoring by integrating Langtrace
with New Relic using OpenTelemetry.

Using Langtrace within Langtrace

A Journey of Building a RAG Application

Implementing RAG using LlamaIndex, Pinecone and Langtrace: A Step-by-Step Guide

Discover how to build a Retrieval Augmented Generation (RAG) system using
LlamaIndex for data indexing, Pinecone for vector storage and retrieval, and
Langtrace for monitoring

Read our blog


BUILT BY A WORLD CLASS TEAM OF BUILDERS FROM




JOIN THE LANGTRACE COMMUNITY

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© 2024 Langtrace. All rights reserved.



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