Together AI is an AI cloud platform built for production AI across inference, model shaping, developer environments, storage, and large-scale compute. The company positions itself as the AI Native Cloud, combining managed infrastructure with systems research to help teams move from experimentation to deployment on open-source and custom models.
Its platform spans serverless and dedicated inference, fine-tuning, evaluations, GPU clusters, managed storage, and sandbox environments for AI development. Together AI supports workloads across text, image, video, audio, code, and multimodal applications, with an emphasis on performance engineering, cost efficiency, and operational control from prototype through frontier-scale training and inference.
Offerings, Capabilities, and Integrations
Together AI provides multiple ways to build, train, shape, and serve AI systems on one platform. Its capabilities cover on-demand and reserved inference, asynchronous batch processing, custom container deployment, self-serve and large-scale GPU infrastructure, managed storage, and tooling for model improvement and evaluation.
The platform is designed to fit modern developer and ML workflows rather than force teams into a single stack. Together AI offers an OpenAI-compatible API, supports a wide range of open-source models and custom models, and integrates with popular application, agent, and retrieval ecosystems including Hugging Face, Vercel AI SDK, LangChain, LlamaIndex, Helicone, Pinecone, MongoDB, Pixeltable, and agent frameworks such as CrewAI, LangGraph, DSPy, PydanticAI, AutoGen, Agno, and Composio.
Products and Services
- Serverless Inference: Fully managed, autoscaling inference for open-source models across modalities through an OpenAI-compatible API, aimed at fast development and production use without infrastructure management.
- Batch Inference: Asynchronous inference for very large workloads, allowing teams to process high-volume jobs against serverless or dedicated deployments more efficiently.
- Dedicated Model Inference: Reserved, isolated inference endpoints powered by the Together AI inference engine for predictable latency, steady traffic, and high-throughput workloads.
- Dedicated Container Inference: Managed deployment for customer-controlled inference containers and runtimes on scalable GPU infrastructure, suited to custom pipelines and generative media workloads.
- Together GPU Clusters: Self-serve GPU clusters with bare-metal performance, InfiniBand networking, persistent storage options, and managed orchestration for training, fine-tuning, and large-scale AI workloads.
- Frontier AI Factory: Custom large-scale AI infrastructure for frontier training and inference projects, spanning high-density GPU capacity, orchestration, observability, and performance tuning at industrial scale.
- Sandbox: Secure code sandbox environments for AI development, with fast startup and resume times, configurable dev environments, snapshots, terminal access, and preview tooling.
- Managed Storage: Managed object storage and parallel file systems optimized for AI workloads, designed to keep compute fully utilized and move data without egress fees.
- Fine-Tuning: Managed fine-tuning for open-source and custom models, including options such as LoRA, full fine-tuning, and preference optimization for production model shaping.
- Together Evaluations: LLM-as-a-Judge evaluation tooling for comparing, scoring, and classifying model outputs through an API or user interface to support production model selection and iteration.
Target Customers
Together AI targets AI-native startups, product teams, and developers building applications that depend on production-grade model performance. Its platform is suited to teams shipping chat, agentic, voice, image, video, search, and coding experiences that need low-latency inference, flexible deployment options, and rapid iteration.
It also serves enterprise ML and platform teams that want to run open-source or custom models with stronger control over performance, privacy, and scaling. On the infrastructure side, Together AI is built for model builders, research groups, and advanced engineering teams that need GPU clusters, storage, and large-scale environments for training, fine-tuning, and frontier-scale AI workloads.
Cloud Integrations and Marketplace
- AWS Marketplace: Together AI is available through AWS Marketplace, giving customers a procurement path for its AI platform and enabling enterprise buyers to align purchases with AWS billing and committed cloud spend.
Key People
- Vipul Ved Prakash: Co-Founder & CEO
- Ce Zhang: Founder & CTO
- Tri Dao: Founder & Chief Scientist
- Charles Zedlewski: Chief Product Officer
- Kai Mak: Chief Revenue Officer
- Percy Liang: Founder
- Chris Ré: Founder
- Meicheng Shi: SVP of Finance
- Albert Meixner: SVP of Engineering
- Mahadev Konar: SVP of Engineering Infrastructure
- Leon Song: VP of Research
- Dan Fu: VP of Kernels
Key Facts
- Headquarters: San Francisco, California, United States
- Employees: 368 employees
- Annual Revenue: $1B annualized
- Parent Company: None
- Subsidiaries: CodeSandbox; Refuel.ai
- Publicly Listed: No
