Cerebras Inference

Groq

The fastest AI inference in the world

An AI infrastructure company that uses LPU (Language Processing Unit) technology to deliver LLM responses at near-instant speeds.

Together AI

The fastest cloud for open-source AI

A cloud platform for fine-tuning and running the world's leading open-source AI models at scale.

Fireworks AI

Production-grade serverless inference platform for open AI models

Fireworks AI is an enterprise AI inference and model serving platform built to run open-weights LLMs, vision models, and multimodal architectures with lightning-fast speeds and lowest cost. Created by former Meta AI and PyTorch infrastructure engineers, Fireworks powers millions of daily AI requests with sub-100ms time-to-first-token (TTFT) and high token throughput. Fireworks allows developers to seamlessly deploy, fine-tune, and serve models like Llama 3.1/3.3, DeepSeek-R1/V3, Mixtral, Qwen 2.5, and Flux.1 with zero cold starts. It uniquely supports instant LoRA fine-tuning switching on shared GPU infrastructure, allowing thousands of custom fine-tuned adapters to run without paying for dedicated hardware.

Modal Labs

Serverless cloud for AI models, batch jobs, and GPU workloads in Python

Modal Labs is a high-performance serverless cloud platform that enables AI engineers and developers to run Python code in the cloud with instant access to thousands of CPUs, GPUs, and persistent network volumes. Founded by former Spotify CTO Erik Bernhardsson, Modal reimagines cloud computing with sub-second cold starts and zero infrastructure configuration. With Modal, you define your container image, dependencies, and GPU hardware directly inside standard Python code using simple decorators (e.g. `@app.function(gpu="H100")`). Modal handles container building, volume mounting, GPU scheduling, and automatic scaling down to zero in milliseconds, making it the premier choice for running generative AI models, ComfyUI video pipelines, and massive parallel batch jobs.

LlamaIndex

Leading data framework for connecting custom data sources to LLMs and Agentic RAG workflows.

LlamaIndex is the premier open-source data framework designed to bridge private, enterprise, and unstructured data with large language models. By providing sophisticated data connectors, automated parser modules, semantic chunking algorithms, and multi-document index structures, LlamaIndex enables developers to build context-augmented LLM applications and autonomous knowledge retrieval engines with minimal boilerplate. From parsing complex multi-page PDF documents and financial spreadsheets to orchestrating complex Agentic RAG workflows that query multiple disparate databases, LlamaIndex handles the complete data ingestion, indexing, and query evaluation lifecycle.

Kestra

Declarative event-driven workflow orchestrator for microservices, AI agents, and data pipelines

Kestra is an open-source, event-driven orchestration platform built to automate and coordinate complex data pipelines, microservices, and multi-agent AI systems. With a modern declarative YAML-first architecture, Kestra enables engineering teams to manage scheduled tasks, webhook triggers, distributed compute jobs, and LLM agent pipelines through code or a rich interactive UI. The platform provides over 600+ pre-built plugins spanning major cloud providers (AWS, GCP, Azure), databases (Postgres, Snowflake, BigQuery), and modern AI ecosystems (OpenAI, LangChain, Hugging Face, Vector DBs). Workflows can execute parallel compute tasks, branch conditionally, manage secrets securely, and handle automated retries with exponential backoff. Kestra eliminates the operational overhead of legacy orchestrators by running statelessly on top of modern container runtimes and Kubernetes, providing real-time workflow visualizers, sub-millisecond execution triggers, and enterprise-grade role-based access control.