Libretto provides automated monitoring, testing, and optimization tools for Large Language Model (LLM) deployments. The platform automatically flags potential errors, generates test sets from production traffic, and creates evaluation criteria to judge model performance. This allows developers to continuously validate prompts and models, ensuring AI quality does not degrade over time.
Funding
$3.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
TGFounders
Product
Problem
Large language model (LLM) prompts often require extensive manual tuning and monitoring to maintain performance and alignment with user intent in production environments. This manual effort is time-consuming and can lead to inconsistent results and reduced reliability of LLM-powered applications.
Solution
Libretto offers a platform to automate the testing, monitoring, and optimization of LLM prompts by analyzing production traffic and user feedback. The platform enables users to generate and test hundreds of prompt variations simultaneously, identifying the best-performing prompts for specific goals. By continuously monitoring user interactions and scoring LLM responses, Libretto helps refine prompts in real-time, ensuring consistent performance and alignment with evolving user needs. The platform automates prompt engineering, reducing the manual effort required to improve LLM reliability in production.
Target Audience
The primary target audience includes prompt engineers, machine learning engineers, and product teams building LLM-powered applications who need to optimize prompt performance and ensure reliability in production.
Features
- Automated prompt generation and A/B testing to identify optimal prompt variations
- Continuous monitoring of production traffic to capture real-world usage patterns
- User feedback integration to understand user intent and identify areas for improvement
- Automated scoring of LLM responses to evaluate prompt performance
- Real-time prompt refinement based on user interactions and performance metrics
- Integration with existing LLM infrastructure for seamless deployment