Flowise vs Haystack Enterprise Platform

Flowise is an open source platform for building generative AI agents and large language model workflows. Its Assistant, Chatflow, and Agentflow visual builders cover assistants, chatbots, single- and multi-agent systems, and workflow orchestration. Listed capabilities include execution logs, visual debugging, evaluations, human review, and retrieval-augmented generation indexing pipelines. Documentation describes connections to more than 100 sources, tools, vector databases, and memories, including LangChain, LlamaIndex, and Zapier Zaps. Developers can use APIs, an embedded chat widget, and TypeScript or Python SDKs. Deployment options include cloud and on-premises setups, as well as self-hosting through npm or Docker. Listed security controls include role-based access, single sign-on, encrypted credentials, secret managers, rate limiting, and restricted domains. The project is winding down: active feature development ceased July 29, 2026; repository archival is listed for August 10; and end of life is August 31, 2026. Source code remains under Apache 2.0. Free costs nothing; Starter costs $35 a month.

Haystack Enterprise Platform is an operational layer for building, evaluating, deploying and governing production AI agents and applications. Teams can assemble and debug agents and retrieval-augmented generation (RAG) pipelines using a visual builder, templates, custom components and retrieval and memory settings. The Playground and Prompt Explorer support comparisons of prompts, retrieval strategies and agent workflows, as well as prototype sharing and feedback. Deployment options include deepset-managed cloud or self-hosting, with serverless autoscaling and a REST API. Governance tools include role-based access, run history, traces, performance monitoring, usage reports and guardrails. The platform lists SOC 2 Type II and ISO 27001 certifications, GDPR and HIPAA compliance, SSO, audit logs, CSA Star Level 1 and pipeline isolation. Listed model integrations include Anthropic, OpenAI, Mistral, Cohere, Gemini and custom models; data-store integrations include PostgreSQL, Snowflake, Qdrant, Weaviate and Pinecone. Pipelines can be exported as Python or YAML, and models and providers can be changed without rewriting code. Studio is free with stated limits; Enterprise pricing is custom and requires contacting deepset.