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LangSmith vs Automi

LangSmith or Automi? A Comprehensive Review

LangSmith

LangSmith

Observability & testing for complex LLM applications.

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Automi

Automi

Create and share custom apps without coding.

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Overview

Description

Introducing LangSmith, a developer platform designed for the complexity of LLM (Language Model) applications. With its comprehensive observability, testing, and evaluation tools, LangSmith

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Introducing Automi - an innovative SaaS platform that allows users to effortlessly create and share custom AI apps without any coding knowledge. With a plethora of top-notch generative AI

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Pricing Options

  • No free trial
  • $0.5, month
  • No free trial
  • Not Available
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Features

Total Features

Features
Features

Unique Features

No features

No features

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Pricing

Pricing Option

      Starting From

      • $0.5, month
      • Not Available
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      View Detailed Pricing

      Other Details

      Customer Types

      • No customer type information available
      • No customer type information available
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      User Reviews

      User Ratings

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      No Reviews

      Pros

      • Observability for LLM apps

      • Testing for LLM apps

      • Open-source SDK

      • Flexible integration

      • Adaptable to different implementations

      • App-level usage stats

      • Real-time behavior monitoring

      • Stochastic nature of LLMs

      • Unit testing facilitation

      • Test datasets creation

      • Transparency emphasis

      • Access to training datasets

      • Provides biases and limitations

      • Data analysis tools

      • Anomaly detection tools

      • Trend forecasting tools

      • Easy adaptability to data

      • Designed by expert team

      • Community-driven development

      • Supports user contribution

      Cons

      • Limited to LLM applications

      • Restricted early access

      • Beta version risks

      • Relies on flexible adaptation

      • No standalone testing environment

      • Stochastic nature uncertainty

      • Requires explicit integration

      • Dataset curation needed

      • Observability depends on adaptation

      • No mention of cross-platform compatibility

      • Lacks pre-made templates

      • No version control

      • Limited model customization

      • No multi-user collaboration

      • Reliance on users' own data

      • No clear support channels

      • Insufficient documentation

      • No SDKs for development

      Media and Screenshots

      Screenshots

      LangSmith
      Automi

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