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Named one of the top 100 AI companies by CB Insights
Named one of the top 100 AI companies by CB Insights
Named one of the top 100 AI companies by CB Insights
Named one of the top 100 AI companies by CB Insights
Named one of the top 100 AI companies by CB Insights
Named one of the top 100 AI companies by CB Insights
Named one of the top 100 AI companies by CB Insights
Named one of the top 100 AI companies by CB Insights
Named one of the top 100 AI companies by CB Insights
Named one of the top 100 AI companies by CB Insights
Named one of the top 100 AI companies by CB Insights
Named one of the top 100 AI companies by CB Insights
Named one of the top 100 AI companies by CB Insights
Named one of the top 100 AI companies by CB Insights
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AI TOOLS
SOLUTIONS
PRICING
ABOUT
OUR MISSION
THE COMPANY
RESEARCH
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Blog
CONTACT
SOLUTIONS
Access our use cases and learn about how Martian can help improve AI performance and cost.
Accelerating RAG Apps
CASE DETAILS
Martian's multi-model routing transformed a major search engine's RAG application, cutting costs while delivering faster responses and higher accuracy, improving their previous state of the art LLM.
Routing for AI Agents
CASE DETAILS
Martian's intelligent LLM routing transformed a financial sector AI agent, boosting a 50-step workflow's success rate while cutting costs, making previously unviable operations economically feasible.
Intelligent summarization
CASE DETAILS
A Fortune 500 telecom company leveraged Martian's multi-model routing system to enhance their videoconferencing, chat, and scientific reasoning applications, outperforming competitors while maximizing value across all platforms.
Customer Service
CASE DETAILS
We transformed a customer service training company's operations by replacing manual simulation creation with an intelligent AI routing system that delivers responses preferred over the top model.
Conversational chatbot
CASE DETAILS
An early stage startup building a chatbot came to us looking to increase margins. We were able to reduce costs by 73.4% by routing to different models while still performing on par to their existing state of the art LLM.
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