deepset, makers of Haystack @deepset_ai
Creators of the @Haystack_AI open source AI Orchestration framework and deepset AI Platform. Build AI with Purpose. deepset.ai Berlin, Germany Joined December 2017-
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š Haystack 2.18 is here! š Pipeline Error Recovery ā resume from the last successful step with snapshots š§ Structured Outputs ā generate Pydantic/JSON schema responses with @OpenAI/@Azure š ļøPipelineTool ā easily expose full @Haystack_AI pipelines as LLM-compatible toolsā¦
š„ Haystack is trending on GitHub⦠again! Itās all thanks to you, the devs who use, contribute, and share ideas. Youāre shaping how AI apps get built for production. ā Add your star and join the community: github.com/deepset-ai/hayā¦
šŖ¢ Integrating Llama Stack and @Haystack_AI to Advance Sovereign Enterprise AI We've integrated @MetaforDevs #LlamaStack with our AI Platform and open-source Haystack Framework, enabling enterprises, government agencies, and defense organizations to accelerate the development ofā¦
ā” ššØš° ššÆšš„š¢ššš„š š¢š§ šššš©š¬šš ššš®šš¢šØ & šš§ššš«š©š«š¢š¬š: šš®š§ ššØš¦š©šØš§šš§šš¬ š¢š§ šš¬šØš„ššš¢šØš§ As AI applications grow in complexity, developers need better tools to debug and validate their agents and workflows efficiently. That's whyā¦
š¤ This week, our CEO Milos Rusic joined the šš®ššØ ššÆšš§š šØš§ šš”š šš©š«šš in Berlin, where leaders gathered to discuss how AI can responsibly transform public administration in light of the 2025 coalition agreement. The discussions spanned public trust,ā¦
š Haystack 2.17 is here with extended multimodality & flexible routing This release expands Haystack's multimodal capabilities and makes core components more powerful and flexible for building dynamic AI pipelines. š¼ļø Image support for more model providers Building on theā¦
š Haystack 2.16 is here with deep debugging for Agents and powerful multimodal workflows. This release is all about developer control and building smarter, more flexible AI apps. š§ Agent Breakpoints Pause execution mid-run, inspect internal state, and resume. Perfect forā¦
𤩠Big news from Baden-Württemberg @RegierungBW: their AI assistant F13 is now open source and built on @Haystack_AI! F13 brings multilingual chat, summarization, and document search to the public sector with data protection built in from day one. š§µ
š„ Haystack 2.15 just landed with faster agents and AI guardrails for safer apps Hereās whatās new š ā” Parallel Tool Calling Agents now run tool calls in parallel. This speeds up agents without needing custom async setups. š”ļø Guardrails with LLMMessagesRouter Use LLMs toā¦
š You can use Gemini 2.5 Pro, Flash, and Flash-Lite with Haystack! š„ Build smart, flexible pipelines and agents with your favorite @GoogleDeepMind Gemini modelāļø š§ Here's when to use which: Gemini 2.5 Pro ā Best for reasoning-heavy tasks and agents Gemini 2.5 Flash āā¦
š¢ Excited to share our new case study with @awscloud and @AnthropicAI featuring MANZ. MANZ Genjus KI is an AI-powered legal assistant that transforms how legal professionals research, analyze documents, and draft contracts. This innovative AI agent: ⢠Thoroughly analyzesā¦
š šš®šššš®š°šø š®.šš° š¶š šµš²šæš² ā šš¶ššµ šæš²š®š¹-šš¶šŗš² š®š“š²š»š šššæš²š®šŗš¶š»š“ š®š»š± š±š²š²š½š²šæ š½š¶š½š²š¹š¶š»š² šš¶ššš®š¹š¶šš®šš¶š¼š»š This release brings powerful upgrades for working with complex agent workflows, visualizing pipelines, andā¦
š¼ļø Building agents that understand both text and images? We've released @Haystack_AI's new experimental Multimodal support, which enables the building of apps that analyze images and PDF documents. Whatās new: šø ImageContent dataclass to pass images in Chat messages š§ Dynamicā¦
š Deploying AI pipelines just got way easier! šš®šššš®š°šø makes it easy to build modular LLM pipelines for agentic apps. Now, with Hayhooks, deploying those pipelines is just as straightforward. š Introducing šš®ššµš¼š¼šøš: an open source deployment layer for Haystackā¦
š ļø RAG may not be the most hyped AI architecture right now. But it remains the one that delivers the most value to users. Gen AI evolves fast, but RAG remains one of the most reliable, scalable, and industry-ready approaches for bringing LLMs into the real world. Whether you'reā¦

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