For developers building GTM and AI agents, Together AI is an inference and GPU-cloud platform that serves 200+ open and open-weight models — built by the researchers behind FlashAttention and Mamba — positioned as a faster, cheaper alternative to hyperscaler inference.
Presence & Market Position
#24 of 122
GTM Developer Tools
▼ 10 60-day move
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
Together AI is working to be the AI-native cloud for teams building on open-weight models, combining inference, dedicated capacity, fine-tuning, and GPU infrastructure with research-led performance work. Its presence is rising across developer and enterprise AI conversations, especially around day-zero model availability, coding-agent workloads, production inference, and the infrastructure behind revenue agents. The record also places the company in customer and ecosystem conversations, hiring narratives, model-launch coverage, and technical events. Together’s own recent activity reinforces that position through new model serving, enterprise-cloud distribution, and large GPU-cluster deployments.
The Washington Post, Cursor, Zomato, Decagon, Cartesia, Pika, Krea, Hedra, Arcee AI
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Business Profile
Together AI has grown from a research-led startup founded in 2022 into an independent provider of inference and GPU infrastructure for open models. It raised an $800M Series C on July 1, 2026, at an $8.3B valuation, with cumulative announced financing of $1.3335B. The company has about 380 employees. Its commercial expansion combines direct relationships with customers such as Cursor and Decagon with infrastructure partnerships, including IBM Cloud. Research remains part of the business model: systems work feeds into the inference, training and dedicated compute services it sells.
Agent Readiness
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
Together AI supports agent builders through its inference API, CLI, and published MCP server for bringing Together documentation and agent skill domains into coding environments. Its product work also includes model serving for coding and agent workloads, dedicated inference, sandboxes for AI applications and agents, and ThunderAgent research for synthetic-data generation. The public build-out spans both the model-serving layer and the tools agents use to develop and operate workloads.
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