Langtail
4.69
0
Langtail simplifies LLM app development with tools for prompt engineering, testing, and deployment in one platform.
What is Langtail?
Langtail is a platform designed to assist in the development and deployment of Large Language Model (LLM)-powered applications more efficiently. It offers various tools for prompt engineering, testing, observability, and deployment, all integrated into a single platform. Users can collaborate with their teams, iterate quickly, and confidently bring their LLM apps to production using Langtail.
Langtail provides features such as a no-code playground for writing and running prompts without coding, adjustable parameters to fine-tune LLM behavior, test suites for preventing surprises in prompts, benchmarking variations to identify top-performing prompt versions, seamless deployment of prompts as API endpoints, detailed logging of performance data and costs, metrics dashboard for aggregated prompt performance metrics, problem detection by monitoring user interactions in production, and a collaborative workflow for team collaboration.
Additionally, Langtail offers a range of pricing plans including a free plan for unlimited users, a Pro plan for growing teams with features like unlimited prompts and 10,000 logs per month, and an Enterprise plan tailored for large organizations with custom features including unlimited logs, SAML Single-Sign-On (SSO), custom billing, dedicated support, and personalized onboarding.
The team behind Langtail consists of the three co-founders: Petr Brzek, Tomas Rychlik, and Martin Duris. They bring their shared success and trust from their previous venture, Avocode, to Langtail. The platform aims to simplify the development and testing of AI, allowing teams to focus on integrating AI features into their products.
Who created Langtail?
Langtail was created by a team of three co-founders: Petr Brzek (CEO), Tomas Rychlik (CTO), and Martin Duris (Growth), who previously worked together at Avocode. The company is based in Prague, Czech Republic. Langtail aims to build innovative tools for debugging, testing, and observing Large Language Model (LLM)-powered applications, helping users develop and deploy these apps faster with tools for prompt engineering, testing, observability, and deployment all in one place.
What is Langtail used for?
- Adjustable Parameters
- Collaborating with team members
- Prompt refinement
- Debugging prompts
- Collaboration on prompts
- Robust evaluation
- No-code playground
- Test suites
- Benchmarking variations
- Seamless deployment
- Collaborative workflow
- Testing LLM-powered apps
- Collaborating with team on prompts
- Robust evaluation of LLM apps
- Writing and running prompts without coding
- Adjusting LLM behavior parameters
- Running tests on prompts
- Deploying prompts as API endpoints
- Monitoring user interactions in production
- Testing prompts
- Observing LLM-powered apps
- Evaluation of LLMs
- Fine-tuning LLM behavior
- Running tests on prompt variations
- Observing AI app behavior
- Iterating quickly
- Deploying LLM-powered applications
- Monitoring production
- No-code Playground for non-technical users
- Seamless deployment of prompts
Who is Langtail for?
- Engineering and AI teams
- Engineering
- AI teams
- AI developers
- Software engineers
- Solutions Engineers
How to use Langtail?
To use Langtail, follow these steps:
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Debug Prompts: Fine-tune prompts and settings to optimize your models' performance quickly. Use advanced features like variables and vision tools built into the platform.
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Testing: Run tests on different prompt versions to prevent surprises and ensure top performance. Benchmark variations to identify the best prompt versions.
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Deployment: Deploy prompts as API endpoints to iterate faster and fit your development workflow. Separate prompt development from app development for more efficient work.
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Monitoring: Monitor production with detailed API logging, metrics dashboard, and problem detection. Identify issues by observing user interactions in real time.
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Collaborative Workflow: Collaborate seamlessly with your team by sharing prompts and working together efficiently.
Langtail offers a free plan with features like writing and running prompts without coding, adjusting model behavior settings, running test suites, deploying prompts across environments, detailed logging, metrics dashboard, and problem detection. Upgrading to the pro plan provides unlimited prompts and logs per month, along with in-app and email support, making it ideal for growing teams. The enterprise plan offers custom features like SAML Single-Sign-On (SSO) and dedicated support, catering to the needs of large organizations.
Pros
- Run tests to prevent surprises, modify prompts, and rely on your test suite to ensure the app's stability.
- Fine-tune adjustable parameters
- Run test suites to prevent surprises
- Seamless deployment of prompts
- Debug prompts, run tests, and observe what’s happening in production.
- Speed up your AI development workflow with Langtail.
- Iterate at Lightning Speed. Fine-tune prompts and settings to optimize your LLM's performance in record time.
- Support for variables, tools (functions), vision, and more built right in.
- See how prompt changes affect your AI's output instantly with an Instant Feedback Loop.
- Roll back to previous prompt versions with full version history.
Cons
- No-code Playground not available
- Seamless Deployment process could be improved
- Benchmark Variations tool could be enhanced for more detailed analysis
- Test Suites for preventing surprises may need more features
- Adjustable Parameters could be more extensive
- No-code Playground is missing, limiting non-technical users
Langtail FAQs
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What is Langtail?
- Langtail is a platform that helps you develop and deploy LLM-powered applications faster. It provides tools for prompt engineering, testing, observability, and deployment – all in one place.
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What are the key features of Langtail?
- Langtail offers features like debugging prompts, running tests, observing production behavior, instant feedback loop, version history, test suites, benchmarking variations, seamless deployment, detailed logging, metrics dashboard, problem detection, and collaborative workflow.
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How can Langtail help in AI development?
- Langtail speeds up AI development workflow by allowing users to debug prompts, optimize LLM performance, run tests, deploy prompts as API endpoints, monitor production behavior, and collaborate efficiently with teams.
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Who are the co-founders of Langtail?
- The co-founders of Langtail are Petr Brzek, Tomas Rychlik, and Martin Duris.
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What are some testimonials about Langtail?
- Users praise Langtail for simplifying prompt refinement, addressing unpredictable behavior of LLMs, enabling team collaboration, and providing robust evaluation capabilities.
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What pricing options are available for Langtail?
- Langtail offers a free plan with limited features, a Pro plan for $99/month with unlimited users and prompts, and a customizable Enterprise plan with additional features like SAML Single-Sign-On, custom billing, and dedicated support.
Get started with Langtail
Langtail reviews
Lara Morrison
February 3, 2025
What do you like most about using Langtail?
The collaborative features foster teamwork, making it easier for us to develop and test prompts together.
What do you dislike most about using Langtail?
I wish the support documentation was more comprehensive; it could use more examples and guides.
What problems does Langtail help you solve, and how does this benefit you?
Langtail helps streamline the AI development process, allowing our team to focus on creating effective solutions without getting bogged down in technical issues.
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Clara Jansen
January 18, 2025
What do you like most about using Langtail?
The no-code playground is a great feature for teams without extensive technical expertise.
What do you dislike most about using Langtail?
Some features are not as intuitive as they could be, which can lead to a learning curve.
What problems does Langtail help you solve, and how does this benefit you?
Langtail enables us to iterate on our AI solutions quickly, which is crucial for staying ahead in the market.
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Matteo Bianchi
February 21, 2025
What do you like most about using Langtail?
I find the prompt engineering tools to be incredibly powerful and intuitive.
What do you dislike most about using Langtail?
The billing system can be a bit confusing at first; a clearer explanation would be helpful.
What problems does Langtail help you solve, and how does this benefit you?
Langtail allows me to develop and refine my LLM applications quickly, which is essential for delivering timely solutions.
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