Exa AI vs Together AI
Side-by-side comparison of AI visibility scores, market position, and capabilities
AI-native search API raised $85M Series B at $700M valuation in Sep 2025 backed by Nvidia and Benchmark; revenue hit $10M with 1,010% YoY growth; powers semantic web retrieval for LLM and RAG pipeline applications.
About
Exa AI is an AI-native search and retrieval company building a fundamentally different kind of web search infrastructure designed specifically for AI systems and developers. Founded on the premise that keyword-based search engines are poorly suited to serve as data sources for large language models, Exa developed a neural search architecture that retrieves web content based on semantic meaning rather than keyword matching — enabling AI applications to find relevant, high-quality information the way reasoning systems think about queries.\n\nExa's API allows developers to perform meaning-based web searches, retrieve full page contents, find similar documents, and access curated data streams for AI training and retrieval-augmented generation pipelines. It is designed as AI infrastructure: the underlying retrieval layer that powers AI agents, research tools, and automated workflows that need accurate, current web information. Target customers are AI developers, research teams, and enterprises building AI-powered products that require reliable web grounding.\n\nExa AI raised $85M in a Series B at a $700M valuation in September 2025, backed by Nvidia and Benchmark Capital. The company's revenue hit $10M with 1,010% year-over-year growth — one of the fastest growth rates in the AI infrastructure category. Nvidia's strategic investment reflects Exa's importance as a retrieval layer in the broader AI stack. As AI agents proliferate and need reliable access to real-time web knowledge, Exa's semantic search API is positioned as essential infrastructure for the next generation of AI applications.
Open-source AI cloud. $300M ARR (Sep 2025). $3.3B valuation. $533M total raised. Backed by Salesforce, NVIDIA, Kleiner Perkins. Founded by ex-Stanford AI researchers.
About
Together AI was founded in 2022 with a mission to build the leading open-source AI cloud—a platform where developers and enterprises can train, fine-tune, and run inference on open-weight models without the constraints and costs of proprietary AI APIs. The company recognized early that as powerful open-weight models like Llama, Mistral, and FLUX proliferated, there was a massive opportunity to provide optimized infrastructure for running and customizing them. Together AI built a multi-cloud GPU platform with custom inference kernels and distributed training optimizations specifically engineered for open-source models.\n\nTogether AI's platform offers fine-tuning, inference, and training services across a curated library of leading open-weight models, with performance-optimized endpoints that often outperform what users can achieve running models on general-purpose cloud infrastructure. The company targets AI engineers, ML researchers, and enterprises that want flexibility—either for cost reasons, privacy requirements, or the need to customize model behavior through fine-tuning. Together's API design closely mirrors OpenAI's, making migration straightforward. Its pricing is consistently below proprietary model APIs for comparable capability tiers.\n\nTogether AI has achieved $300M in annualized revenue as of September 2025, growing to a $3.3B valuation with $533M in total funding. Investors include NVIDIA, Salesforce, and Kleiner Perkins—a combination that provides both strategic GPU supply chain relationships and enterprise go-to-market leverage. The open-source AI cloud market is a significant and growing segment as enterprises prioritize model flexibility and cost control alongside the maturation of open-weight models that increasingly compete with frontier proprietary models.
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