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Langtail is a prompt management platform designed for product teams, specifically engineered to simplify AI prompt engineering. It supports team collaboration in building, testing, and deploying AI prompts, enabling end-to-end control of AI workflows from conception to production.

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What is Langtail?

Langtail is an LLMOps (Large Language Model Operations) platform designed for product, engineering, and business teams, helping accelerate AI application development and deliver more reliably into production environments. It offers full lifecycle management—from prompt experimentation, testing, and deployment to real-time monitoring—while enabling non-technical users (e.g., those familiar with spreadsheets) to participate in prompt management without coding. Additionally, it provides comprehensive prompt control features such as natural language evaluation, pattern matching, and custom code validation. By leveraging data-driven insights, it optimizes models, parameters, and prompt combinations, and can be self-hosted to ensure maximum security and data sovereignty.

Key features

  • Collaborative Prompt Development: Work together in a visual Playground environment to experiment with, debug, and iterate on prompts, boosting team collaboration efficiency; it supports seamless multi-role collaboration among product, engineering, and business stakeholders.

  • AI Firewall: With one-click integration, it instantly blocks prompt injection, denial-of-service attacks, and information leaks, while supporting custom content filtering rules and real-time threat alerts.

Use cases and audience

An AI collaboration platform tailored for product, engineering, and business teams—extending beyond developers to include non-technical roles such as marketing in co-creating prompts.

  • Build, test, and deploy AI prompts, supporting product teams throughout the entire workflow—from proof-of-concept stages to production environments.
  • Validate and optimize prompts through natural language evaluation, pattern matching, or custom code
  • Monitor user input and model responses in real time, analyzing key metrics such as latency and cost to improve efficiency
Input

User-input text—such as email content or chat messages—can be imported in bulk via sample files or integrated in real time through application requests.

Output

Model response content after prompt processing, performance test results, real-time monitoring data (including latency, cost, and success rate), along with visualized analytical charts.

Frequently asked questions

What happens if you exceed your plan’s usage limits?

When the planned usage limit is exceeded, the system will notify you based on actual usage and may restrict the service.

What are logs, and how are they counted?

Logs refer to the log records generated by each prompt invocation, counted monthly; for example, the free plan includes 1,000 logs per month.

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