Airbyte

Airbyte 2.0 is live! 🎉 We spent the last year+ completely reimagining what data movement should be in the AI era. This is the result. No more choosing between cloud simplicity and keeping your data sovereign. No more warehouse insights trapped where teams can't use them. No more waiting hours for syncs that should take minutes. It's not an incremental improvement. It's a platform that works in an era where the old rules no longer cut it. When every company is becoming an AI company, data infrastructure can't be the bottleneck. See what we built: https://airbyte.com/v2

Event season is in full swing for the Airbyte team! We just wrapped up the Chicago stop of the Snowflake World Tour. Thanks to everyone who came by our booth to talk with our experts! 📍 Find our team next week in Las Vegas! 🥇 We're thrilled to be a Gold sponsor at Coalesce, where we’re bringing the fun AND the insights. Connect with us at booth #315 for demos, swag, and top-notch conversations, plus join our session from VP of Engineering, Charles Giardina. 🔗 https://bit.ly/3FjgVYh 🥂 Meet us for a drink after the Coalesce Welcome Reception! We're teaming up with our friends from Hex, Snowflake, Datadog and AWS at Redtail for an evening of no-pressure fun. 🔗 https://bit.ly/4nC30RH See you soon! 👋

Symend saved $900K annually while powering AI-driven debt recovery for 200M+ customers. ⚡️ By creating personalized digital experiences, Symend improves collection rates, lowers cost-to-collect, and increases customer lifetime value. But scaling its impact meant overcoming major data infrastructure challenges. With a growing customer base and ambitious AI goals, Symend's engineering team needed more than a legacy data pipeline tool could offer. By partnering with Airbyte, Symend gained: 🟣 Distributed architecture that eliminates cascading failures across client pipelines 🟣 Streamlined setup and scalability with fast deployment and flexible configuration 🟣 Easy-to-manage connectors for Microsoft SQL, unstructured data in S3/Blob, and other enterprise sources 🟣 Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend 🟣 Ability to create simpler, more consistent pipelines that scale with their business This has resulted in: 🔵 Symend projects cost savings of approximately $900,000 annually by migrating from Azure Data Factory to Airbyte. 🔵 Reduced data refresh latency from 2 hours to as little as 30 minutes, significantly improving SLAs and customer commitments 🔵 Eliminated cascading pipeline failures with Airbyte's distributed architecture, enabled by parallel processing of multiple client data streams 🔵 A self-service AI-powered chatbot via Snowflake Cortex that helps business users ask data questions in natural language without technical assistance

OpenAI is having its App Store moment 💥 AgentKit, Sora 2, Apps in ChatGPT - we’re getting closer to the promise of a fully agentic world!!! I’m all in on AI and what we can achieve with this awesome new technology. But as a data guy, I have to talk about the boring (but super important) stuff - governance and sovereignty. Some enterprises may be concerned about sharing data through an external vendor. But they also want to adopt new tools and innovate. How do you innovate safely? Build AI inside your own environment - potentially with OpenAI’s new open source weights! Innovation and sovereignty aren't mutually exclusive. You just need the right infrastructure.

Legacy platforms are expensive and difficult to use. Enterprise Flex is the most adaptable deployment model for global enterprises. At a cost that doesn't set your business back. 🙌 Separating the control plane from the data plane ensures data sovereignty and compliance for organizations and offers untold flexibility and control. Learn more: https://bit.ly/48abuuz

AI just hit a wall 🧱 And your proprietary data is the way through it. Mistral AI's CEO confirmed what we've been seeing: publicly available training data is exhausted. Models trained on the open internet have plateaued. The next wave of AI innovation won't come from bigger models. It'll come from companies training AI on their own first-party data. 🫸 Here's the shift: Public data → saturated Proprietary enterprise data → the new frontier Generic AI → domain-specific intelligence built on your operational reality But there's a catch: you can't send decades of sensitive business data to external platforms and hope for the best. To unlock this, enterprises need data sovereign infrastructure that lets you train AI models on proprietary data while keeping everything in your own environment with full control, compliance, and security. The companies that figure this out won't just use AI better. They'll have AI no one else can replicate!!! https://rb.gy/l0vvo9

Adopting AI is about breaking habits. Even the ones we love. The easy wins? Tasks we hate: 📝 Going from bullets to paragraphs (AI does it faster) 🔍 Sales research (deep search wins) 🧪 Writing tests (LLMs crush it) But here's the hard truth: going “all in on AI” means rethinking work we actually enjoy. For me, that's product building. I love it. Always have. But today, large parts of what I used to do manually? AI handles them better. Even the fun parts!!! Breaking that habit is uncomfortable, but necessary. What work do you love doing that AI does better?

🪩 We're about to bring the (data) party to Las Vegas. Connect with our technical experts at Coalesce 2025 to chat all things data activation. 🎤 At Coalesce, our VP of Engineering Charles Giardina will break down how they consolidated everything onto Airbyte + dbt during his session "One platform, two-way value: How data activation drives business impact." Data teams are tired of stitching together multiple tools for what should be a single workflow. 💤 Case in point: A leading life sciences company was bleeding budget on a vertically-focused platform that only solved half their problem. They needed ELT to get data into their warehouse AND reverse ETL to push insights back to business tools. Two vendors. Two contracts. Double the overhead. Learn more from Charles IRL! The fun doesn't stop there! Stop by booth #315 to dive deeper with our experts! Our top experts are on site to chat about your use cases, including how to get the right data into your AI products. More event info: https://bit.ly/46LKVtb

🎉 Honored to say Airbyte has been included in Database Trends & Applications Big Data Quarterly’s #BigData75 list! https://bit.ly/4mGFNMQ

Steven Vaughan-Nichols asks the right question in Open Source Watch: "How do you keep your cloud data safe if you want to use it in an external AI program?" Enterprise Flex provides an answer by letting companies manage integrations in the cloud while actual data stays within their secure infrastructure. The regional compliance angle he highlights is key: sensitive data remains within your regional infrastructure, meeting location-specific regulatory requirements. EU data stays in EU. APAC data stays in APAC. As Steven notes, this addresses one of the problems keeping AI from being more useful - the inability to safely use private data. Thanks, Steven, for the thorough breakdown of how Enterpride Flex delivers data sovereignty and cloud flexibility for enterprises deploying AI and analytics at a global scale! https://bit.ly/4nVLyaB