Haystack
Also known as: deepset, Haystack
Open-source LLM orchestration framework by deepset for building RAG, search, and agentic pipelines, with enterprise support.
Haystack is an open-source Python framework, built by the company deepset, for building production-ready applications powered by large language models. It is one of the older projects in this space, launched in 2020 with deep roots in classical search and natural-language processing, and that heritage shapes its character: where some frameworks are LLM-first, Haystack treats an AI application as a search-and-orchestration problem first and a model problem second. Its guiding idea is explicit control over how information is retrieved, ranked, filtered, combined, and routed before it ever reaches the model.
The core abstraction is the pipeline. Developers assemble applications from modular components, each responsible for a specific task such as retrieval, indexing, ranking, tool calling, memory, generation, or evaluation, and connect them into a directed graph where the data flowing between steps is typed, inspectable, and traceable. There are no prompts; every step is visible. A 2024 rewrite to version 2 added typed connections and a pipeline runtime that supports branches, loops, and cycles, which is what lets the same architecture express both straightforward retrieval flows and agent loops with conditional logic.
Haystack's strongest territory remains retrieval-augmented generation and search. It supports hybrid retrieval that combines keyword and vector methods, reranking, metadata filtering, and integrations with many document stores, so teams building search assistants over large document collections can tune the retrieval path precisely. On top of that foundation it supports agents with standardized tool calling, multimodal applications beyond text, question answering, and document-processing workflows.
The framework is deliberately model- and vendor-agnostic, integrating with providers like OpenAI, Anthropic, Mistral, Cohere, Hugging Face, Azure OpenAI, and AWS Bedrock as well as local models, so teams can swap models or infrastructure without rewriting their system, and it supports newer standards such as the Model Context Protocol for tools. Pipelines are serializable and cloud-agnostic with logging and monitoring, designed to deploy across cloud and on-premises environments. deepset also offers a commercial Haystack Enterprise Platform built on the open-source core, adding managed deployment and evaluation for teams operating these systems at scale.
Vendor details
Canonical URL
https://haystack.deepset.ai/
Category
Agent infrastructure
Company status
independent
Use cases & customers
Target customers
Deployment options
In practice
You're building a search assistant over millions of documents and need precise control of the retrieval path. Haystack's typed pipelines let you compose hybrid retrieval, filtering, and reranking explicitly before anything reaches the model.
You want an agent whose every step is visible, not behind a high-level abstraction. Haystack exposes retrieval, tools, memory, and generation as inspectable components in a directed graph you wire together yourself.
You need to deploy the same LLM application across clouds and on-prem without rewrites. Haystack pipelines are serializable and vendor-agnostic, so you can swap models or infrastructure and run anywhere with logging and monitoring.
Agentic Index coverage score
9.5 / 14 capabilities · 68%
| Integrations & Tool CallingAgentic AI Index Expansion Evidence Report | Full |
|---|---|
| Workflow OrchestrationAgentic AI Index Expansion Evidence Report | Full |
| Knowledge Grounding & RAGAgentic AI Index Expansion Evidence Report | Full |
| Human Oversight & GuardrailsAgentic AI Index Expansion Evidence Report | Unable to verify |
| Security, Identity & GovernanceAgentic AI Index Expansion Evidence Report | Partial |
| Observability & AuditabilityAgentic AI Index Expansion Evidence Report | Partial |
| Memory & State PersistenceAgentic AI Index Expansion Evidence Report | Full |
| Deployment & Data ResidencyAgentic AI Index Expansion Evidence Report | Full |
| Prebuilt Agents, Templates & PacksAgentic AI Index Expansion Evidence Report | Partial |
| Triggers & Channel CoverageAgentic AI Index Expansion Evidence Report | Partial |
| Model Flexibility & RoutingAgentic AI Index Expansion Evidence Report | Full |
| APIs, SDKs & MCP ExtensibilityAgentic AI Index Expansion Evidence Report | Full |
| Testing, Debugging & OptimizationAgentic AI Index Expansion Evidence Report | Partial |
| Browser & Computer UseAgentic AI Index Expansion Evidence Report | Unable to verify |
The Agentic Index coverage score grades every vendor Full, Partial or Unable to verify against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded
Recent platform changes
Haystack 2.30.2 prevents Agent from exiting prematurely when an invalid tool call is discarded; the model can continue looping and recover.
Bears on: Agent capability
View sourceHaystack 2.30.1 lets AzureOpenAIChatGenerator accept Secret values for azure_endpoint and api_version, enabling environment-variable-based runtime switching.
Bears on: Deployment / data residency
View sourceHaystack v2.30.0 added PythonCodeSplitter for syntax-aware Python code splitting in code-RAG/code-search pipelines; allowed ChatGenerator components to accept plain strings as messages; updated DALL-E image generation defaults for OpenAI's newer image models; added async retriever support; and fixed an Agent bug where multiple tool calls could prevent the configured exit condition from stopping the loop.
Bears on: Workflow orchestration
View sourcePricing
OSS free; Enterprise flex-priced
hybrid
Included quota
OSS/Community (free): modular Python pipelines + agent workflows, 150+ components, hybrid retrieval, multimodal RAG, tool calling, native evaluation (RAGAS/DeepEval), serializable cloud-agnostic deployment, community support. Enterprise Starter adds best-practice pipeline/deployment templates, direct private support from the Haystack maintainers, and access to services. Enterprise Platform adds a no-code visual pipeline builder, autoscaling, monitoring/observability, collaboration, governance/access controls, and SOC 2 security.
What is public
Haystack (haystack.deepset.ai, by deepset - open-source AI orchestration framework for production RAG, agents, and search in Python) is free under an open-source license (no licensing fees). deepset layers three commercial tiers on top: Haystack OSS / Community (free), Haystack Enterprise Starter (support + private guidance + enterprise templates, priced by organization size), and the Haystack Enterprise Platform (full managed/self-hosted toolset - visual pipeline editor, observability, governance, autoscaling; custom-priced, with a free trial). Enterprise pricing is custom and based on org size.
Billing mechanics
Dual-track: the Haystack framework is free OSS (you pay only your own infra + LLM/vector costs). Commercial revenue comes from (1) Enterprise Starter - a support/services + templates layer priced 'simply, based on the size of your organization'; and (2) the Enterprise Platform - priced around platform licensing + agent/application runtime + any expert services, custom-quoted for cloud, hybrid, VPC, on-prem, or air-gapped deployments. A free trial of the Enterprise Platform is available.
Cost watchouts
On OSS you still pay infra, LLM tokens, and vector-DB usage yourself; Enterprise Starter/Platform prices aren't publicly listed (org-size and runtime-based, quote-only); expert-services/consulting hours are an additional line; on-prem/air-gapped deployments carry higher setup overhead
Variable cost rationale
OSS spend is fully usage-based (your own infra + LLM/vector); Enterprise Platform adds a licensing + runtime model where agent/application runtime and expert services scale the bill, so cost grows with deployment scale and support depth
Additional watchouts
Code-first/Python framework - strong control but requires engineering skill (newcomers face a learning curve vs fully managed tools); commercial pricing is entirely quote-only; limited presence on B2B review sites; OSS 'free' still means you own infra + model costs
Overage / add-ons
OSS imposes no caps (cost = your infra + model/vector usage). Enterprise Starter scales by organization size; Enterprise Platform cost scales with platform licensing + agent/application runtime + expert-services hours; deployment environment (cloud/VPC/on-prem) affects the quote.
Sales call required
Mixed (some tiers require a call)
Free / trial
OSS free; Enterprise Platform free trial
Lowest paid plan
OSS free; Enterprise Support flex-priced
Commercial notes
Built by deepset (Berlin; founders Malte Pietsch, Milos Rusic, Timo Moeller; ~$45M+ funding incl. Series B; Gartner Cool Vendor); industry-standard OSS RAG/agent framework; 'sovereign AI' positioning (run/govern agents in any environment, no vendor lock-in); used by Airbus, Lufthansa, NVIDIA, Comcast, Netflix, the European Commission, and other public-sector/defense orgs
Key ambiguities
No public dollar figures for Enterprise Starter or Enterprise Platform - 'based on organization size' and runtime/services scope, quote-only; the Enterprise Platform was previously 'deepset Cloud' (naming/packaging evolved); limited third-party pricing data exists
Cancellation / refund
OSS is free (open-source license, no contract); Enterprise Starter is a paid support/services subscription sized to your org; Enterprise Platform is custom-contracted with a free trial; deployment can be managed cloud, VPC, on-prem, or air-gapped
Support SLA / resale
Community support (OSS/Discord/GitHub); Enterprise Starter adds direct private support from the Haystack maintainers + templates (4 hrs/month consultation, email channel, 6-month extended version support); Enterprise Platform adds SOC 2 security, governance/access controls, monitoring, autoscaling, and embedded expert services; model/vendor-agnostic (OpenAI, Anthropic, Mistral, Cohere, Hugging Face, Azure OpenAI, AWS Bedrock, Weaviate, Pinecone, Elasticsearch)
Missing data
Enterprise Starter and Enterprise Platform have no public list pricing (org-size + runtime + services based, quote-only). Seed 'OSS framework free; Enterprise Support flex-priced; Enterprise Platform free trial' is accurate - Enterprise Starter is sized by organization, and the Enterprise Platform is custom-priced with a free trial.
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Alternatives to Haystack
The closest documented capability profiles to Haystack among agent infrastructure platforms tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.
- Letta10.0 / 14Adds documented Human Oversight & Guardrails
- LlamaIndex9.0 / 14Adds documented Human Oversight & GuardrailsHaystack vs LlamaIndex →
- Langbase7.5 / 14A lighter documented profile than Haystack
- LangChain11.5 / 14Adds documented Human Oversight & GuardrailsHaystack vs LangChain →
- Toolhouse7.5 / 14A lighter documented profile than Haystack
- xpander.ai10.5 / 14Adds documented Human Oversight & Guardrails and Browser & Computer Use
Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded