Haystack

HaystackSince 2026-08

Haystack is an open-source NLP and generative AI framework by Deepset, designed for building production-grade Retrieval-Augmented Generation (RAG), neural search, and multi-modal question-answering systems. Built with modular component architecture, Haystack allows engineering teams to assemble and customize search pipelines using diverse document stores, embedding models, and LLMs. With enterprise features like hybrid search (dense vector + sparse BM25 retrieval), advanced cross-encoder re-ranking, and structured pipeline validation, Haystack powers mission-critical search engines at global enterprises.

Haystack 2.0 provides a component-driven pipeline architecture where developers connect discrete nodes (DocumentStores, Embedders, Retrievers, Rankers, and Generators) into clean Directed Acyclic Graphs (DAGs). Pipelines can be serialized to YAML for continuous integration, tested locally, and deployed via REST API with Haystack service templates. Haystack integrates natively with all major vector databases, including Qdrant, Pinecone, Milvus, Weaviate, and OpenSearch, providing full vendor flexibility without vendor lock-in.

RunPodSince 2022

RunPod is a leading globally distributed GPU cloud and serverless computing platform engineered specifically for artificial intelligence workloads. It provides developers, AI researchers, and enterprises with on-demand access to top-tier NVIDIA GPUs (including H100, A100, L40S, and RTX 4090) at up to 80% lower cost than traditional legacy hyperscalers.

With RunPod Serverless, developers can deploy production-ready AI endpoints with zero idle server costs, sub-second cold starts, and automated scaling. RunPod also offers pre-configured one-click templates for DeepSeek-R1, vLLM, ComfyUI, Stable Diffusion, Ollama, and PyTorch, making it the premier infrastructure choice for deploying modern open-source models.