LLM developers face many challenges that hinder the ability to quickly build and scale high-quality products that people love:
Time-consuming infrastructure setup and maintenance for deploying and scaling LLM applications
Difficulty collaborating on prompt engineering and evaluating models for specific use cases
Challenges monitoring and ensuring consistent performance in production for optimal user experience
Tedious process of creating datasets for fine-tuning and iteratively improving output quality
Keywords AI is built for developers. It has every feature needed to build, deploy, and scale LLM applications:
Infrastructure and Deployment
OpenAI-compatible integration with 2 lines of code
Supports 100+ LLMs with built-in load balancing, error handling, and dynamic routing
Model Playground
Interactive playground for comparing prompts and A/B testing different models
Find the best LLM for your use case through experimentation and evaluation
Prompt Management
Intuitive prompt management system for versioning and deploying prompts
Collaborative workspace for teams to share and iterate on prompts
Request Logging
Request logs for tracing and debugging user-model interactions
Automated output evaluation for detecting hallucination and other quality issues
Performance Evaluations
Comprehensive evaluations to compare model performance with customized metrics
Monitor response quality over time to build product confidence
Usage Dashboard
Real-time monitoring of model performance and user analytics
Comprehensive overview of product usage trends and user behavior
User Analytics
Track growth, retention, and unit economics with detailed usage analytics
Sentiment analysis and topic/intent classification for user insights
Data Curation and Fine-Tuning
Easily collect and curate production golden dataset for model optimization
One-click model fine-tuning for improved performance and cost savings
Andy and Raymond both studied mechanical engineering at UIUC and have been best friends since college.
Andy took a gap year to work as a product design engineer at Apple after freshman year, where he designed parts for the next-gen & next-next-next-gen AirPods. He dropped out after realizing his dream job wasn’t that fun.
Raymond is so good at learning things. He graduated with the highest honor in just three years and self-mastered software engineering within a year. He dropped his robotics PhD offers from top schools.
We’ve worked on a bunch of very bad ideas together in the past year. Now we think we've stumbled upon a good one :)
Get started free with $15 in credits
Chat with us if you’re building with LLMs - we’d love to be helpful
Join our Discord community of AI builders
API Bartender for LLMs