LastMile AI - Ship generative AI apps to production with confidence.

LastMile AI Ship generative AI apps to production with confidence.

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#RAG
#AI development
#AI apps production
#debugging AI
#evaluating AI
#enterprise AI systems

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What is LastMile AI?

LastMile AI is designed to facilitate the development and deployment of generative AI applications. The platform offers tools for debugging and evaluating Retrieval-Augmented Generation (RAG) pipelines, versioning and optimizing prompts, and model management. Key features include the Auto-Eval for detecting hallucinations in AI outputs using specialized evaluator models, RAG Debugger for inspecting RAG applications, and AIConfig for prompt and model optimization.

With LastMile AI, users can connect their data safely to Large Language Models (LLMs), manage performance across system pipelines, and optimize AI operations with controls for versioning and custom evaluator models tailored to specific needs.

Features

Auto-Eval: Detect and benchmark hallucinations in RAG outputs using small evaluator models.
RAG Debugger: Debug and inspect RAG apps, improve system performance through comprehensive evaluations.
AIConfig: Version control, prompt optimization, and parameter management for AI models.

Use Cases

Deploying RAG applications in production environments
Benchmarking and customizing evaluator models for enterprise AI systems
Optimizing AI prompts for varied models and modalities

FAQs

What is LastMile AI used for?

LastMile AI helps developers transition generative AI applications from prototype to production with tools for debugging, evaluating RAG pipelines, and model management.
What are the key features of LastMile AI?

Key features include Auto-Eval for detecting hallucinations in AI outputs, RAG Debugger for inspecting RAG applications, and AIConfig for prompt and model optimization.
What are some use cases of LastMile AI?

LastMile AI can be used for deploying RAG applications in production environments, benchmarking evaluator models, and optimizing AI prompts for different models and modalities.