Future AGI is an AI lifecycle platform designed to support enterprises throughout their AI journey. It combines rapid prototyping, rigorous evaluation, continuous observability, and reliable deployment to help build, monitor, optimize, and secure generative AI applications.
Data can be added manually, via file upload, SDK, or imported from Hugging Face. See the Adding Dataset section.
What are dynamic columns?
Dynamic columns allow you to generate new data based on existing columns using prompts, API calls, code execution, etc. Learn more in Create Dynamic Column.
Tracing provides detailed visibility into the execution flow of your AI applications, helping debug issues and understand performance. See the Tracing Overview.
Which frameworks support auto-instrumentation?
We support auto-instrumentation for frameworks like OpenAI, Langchain, LlamaIndex, and more. See Auto Instrumentation.
How does Future AGI help optimize prompts or models?
Optimization provides a structured, iterative approach to refining AI-generated outputs by systematically improving prompts. Unlike experimentation, which focuses on testing multiple prompt variations, optimization enhances prompt by adjusting its structure based on evaluation-driven feedback. See the Optimization Overview.