deepset provides a platform for building, testing, and deploying generative AI in mission-critical business applications.

deepset

For teams in need of optimizing their time and resources, our enterprise LLM platform, deepset Cloud, lets you design, securely deploy, and monitor your AI applications leveraging pre-built components and a unified development environment. Since 2018, we have enabled organizations across the financial, manufacturing and legal industries to unlock the potential of natural language processing for their business use cases. If you can dream it, you can build it with deepset Cloud.

Since 2018, deepset has helped AI teams to apply the latest in NLP to real-world applications. We also provide Haystack — a trusted, reliable open-source technology to build standalone applications with LLMs.

System.One

Tiny VC

Lunar Ventures

Acequia Capital (AceCap)

Charlie Songhurst

Jeremy Yap

Rand Hindi

Google Ventures

Harpoon

Alexander Ratner

Emil Eifrem

Mustafa Suleyman

Spencer Kimball

Balderton Capital

🏗️ There's been a lot of talk lately about Compound AI - a design principle for building AI products that emphasizes systems thinking over individual models to maximize AI results. 


💅 𝐓𝐮𝐫𝐧𝐬 𝐨𝐮𝐭, 𝐝𝐞𝐞𝐩𝐬𝐞𝐭 𝐚𝐧𝐝 𝐨𝐮𝐫 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫𝐬 𝐡𝐚𝐯𝐞 𝐛𝐞𝐞𝐧 𝐩𝐢𝐨𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐜𝐨𝐦𝐩𝐨𝐮𝐧𝐝 𝐀𝐈 𝐩𝐫𝐨𝐝𝐮𝐜𝐭 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 𝐟𝐨𝐫 𝐲𝐞𝐚𝐫𝐬.


✨ Our latest blog post explains the advantages of Compound AI and its role in creating lasting, scalable products and processes. ✨


https://lnkd.in/dqG2j74H

🌟 What an incredible roundtable event! 🌟

Grab a Byte Berlin was an amazing experience together yesterday. A huge thank you to guest speaker, Sebastian Horn, for sharing your journey and insights about building Generative AI into the consumer and journalist experiences at ZEIT ONLINE with speed and trust – and to our amazing group of attendees representing AI change makers across the media and publishing industry. Your questions, insights and vibrant discussions were truly inspiring!

We’ll be continuing the Grab a Byte roundtable series in the near future to cover:
✅ Best practices to ensure user trust and AI accuracy
✅ Innovative ways to incorporate customer feedback into AI products
✅ Approaches to optimize the diversity of user interactions
✅ Getting AI into production to drive value, learning and optimization.

Stay tuned for next dates and locations! Thank you for sharing your morning and valuable contributions with us Ludwig Siegele, Anne Küpper, Carlo Speth, Julian Oliver Chudoba, Torben Brodt, Katharina Neubert, Dr. Sebastian Wernicke, and Christian Palm!  See you again soon!

#AI #Media #Publishing #Innovation #UserTrust #AIAccuracy #ProductionAI #Berlin

Webinar - Building LLM-Powered Customer Experiences in 120 Days 👇 
[Accelerating AI in Publishing]

Sign up here: 
https://lnkd.in/gs9RCzXy

Facing AI implementation roadblocks? Join YPulse President Dan Coates in our upcoming webinar as he shares how his team used deepset Cloud to develop a groundbreaking Generative AI product in just 120 days.

In this session, you'll learn:

-> The secret sauce: Discover the strategy they used to overcome common AI adoption challenges and launch quickly.

-> Focusing on what matters: Identify high-impact use cases that deliver real business value.

-> Building to last: Learn how deepset Cloud enabled YPulse to establish a scalable technical foundation for AI implementation.

Don't miss your chance to replicate YPulse's success! Gain the insights you need to make AI a reality for your business.

#AI #GenerativeAI #Webinar #Business #Innovation #YPulse

We’re excited to welcome Mathis Lucka, Vice President of Product at deepset to the stage at Ai4 2024 on August 12-14 at the MGM Grand in Las Vegas! Join the discussion around “From Prototype to Adoption: Building AI Products That Stick.” Register now: https://lnkd.in/e6dTnzj9

💡 At deepset, we’re always excited to test and support new innovations and customizations to get the most out of AI.

Microsoft recently open-sourced the GraphRAG framework for information retrieval, utilizing graph-based structures. It automates the construction of knowledge graphs using LLMs and enhances retrieval by connecting related concepts and entities in a query for more contextual and accurate responses.

GraphRAG offers a larger connected context for retrieved information, which LLMs use to answer summarization-focused queries. It does not replace RAG but can significantly augment existing information extraction pipelines.

Asking questions on financial data is one example of a great use case for GraphRAG.
 
🔎  Check out this demo comparing quarterly earnings call transcripts from a few companies to see a side-by-side comparison: https://lnkd.in/g_zj6WVu

💬  Ready to see GraphRAG in action on your data? Book a deepset Cloud Demo today: https://lnkd.in/g5Zzn8UH

📚 Learn more about about GraphRAG on deepset's blog: https://lnkd.in/g9VxpDKd

🚀 Benchmarking RAG Pipelines for Optimal Performance!

The latest article by David S. Batista, PhD, breaks down step-by-step instructions to evaluate and optimize your RAG pipeline's performance using Haystack, complete with detailed benchmarking against the ARAGOG dataset.

🌟 Key Highlights:
- Explore three different Haystack pipelines: indexing, RAG, and evaluation.
- Gain insights from the “ARAGOG: Advanced RAG Output Grading” dataset.
- Learn how to fine-tune parameters like top_k, embedding_model, and chunk_size.
- Discover the best-performing combinations for context relevance, faithfulness, and semantic answer similarity
- Detailed analysis and lessons learned to help you achieve the best performance for your use case

Read the full article 👉 https://lnkd.in/d-2NmawF

#rag #opensource #evaluation #haystack

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