Arango

💫 Welcoming Daniel Morris to Arango We’re thrilled to welcome Daniel Morris to Arango as our newest Solutions Engineer! 🎉 Daniel joins us at an exciting moment in our journey — as Arango continues to grow and scale as the leading AI Data Platform built to power the next generation of Contextual AI applications. As we expand globally, Daniel’s expertise will help our customers unlock the full potential of multi-model and multimodal data — building context-aware AI co-pilots, chatbots, and agents that deliver accuracy, scalability, and better economics. At Arango, we’re building more than a product — we’re building a world-class team shaping the future of enterprise AI. 🚀 Welcome aboard, Daniel — we’re excited to have you on this journey with us! 🙌 #Arango #AIDataPlatform #ContextualAI #TeamArango #Growth #Innovation #Hiring #GraphRAG #AIInfrastructure

AI doesn’t fail because of the model. It fails because of the data underneath it. And most enterprises are learning this the hard way. The moment AI moves from a prototype to a real product, everything that was “good enough” in the data layer starts to crack: • Too many systems to integrate • Too many pipelines to maintain • Too many versions of the truth • Too much latency between where data lives and where AI needs it So instead of asking, “How do we add more AI?” Leaders are now asking: 🟢 “How do we fix the foundation AI depends on?” Forrester’s latest report hits this head-on: Multimodel Data Platform: The Missing Layer in Your AI Stack It lays out why modern AI requires graph, vector, document, and transactional context in one place — and why the “polyglot database era” is falling apart under real-world scale and complexity. It also highlights a clear market shift: ✅ Enterprises like NVIDIA, Siemens, Synopsys ✅ AI-native builders like Articul8 …are modernizing the data layer before scaling AI — not scrambling to fix it once models are already in production. If you’re a CTO, CPO, or engineering leader responsible for delivering AI that’s accurate, explainable, and production-grade, this report is a must-read. 🔗 https://lnkd.in/gAXEEcns Comment if you want a quick summary — happy to DM it.

🚀 Arango Is Growing — And We’re Hiring AI ❤️ Context. But today’s fragmented data infrastructure loses it. That’s why so many organizations are stuck in the AI Failure Zone — where powerful models operate without business understanding. At Arango, we’re changing this with a Contextual AI Data Infrastructure powered by a unified System of Context. We capture relationships, semantics, lineage, provenance, and operational signals — with governance, security, and compliance built in. This gives enterprises the foundation to run AI that is accurate, explainable, scalable, and economically efficient. To support this momentum, we’re expanding our GTM and technical organizations and looking for talented people who want to help shape the future of enterprise AI. We’re hiring across our GTM organization: Marketing • Sales • Partnerships • Federal GTM And across the company in: Engineering • Professional Services • Sales Engineering • EMEA Sales • Internships Whether you’re passionate about building AI-powered products, driving world-class GTM programs, or helping customers succeed, there’s a place for you here. 🔎 Explore all open roles: https://lnkd.in/guyfbdUT If you know someone who would be a great fit, please share or tag them below. Arango | AI Data Platform Help us build Contextual AI — AI that understands your business. #AIcareers #ContextualAI #TechJobs #MarketingJobs #SalesJobs #EngineeringJobs #Partnerships #FederalGTM #ArangoAI #Hiring

🚀 Arango Is Growing — And We’re Hiring AI ❤️ Context. But today’s fragmented data infrastructure loses it. That’s why so many organizations are stuck in the AI Failure Zone — where powerful models operate without business understanding. At Arango, we’re changing this with a Contextual AI Data Infrastructure powered by a unified System of Context. We capture relationships, semantics, lineage, provenance, and operational signals — with governance, security, and compliance built in. This gives enterprises the foundation to run AI that is accurate, explainable, scalable, and economically efficient. To support this momentum, we’re expanding our GTM and technical organizations and looking for talented people who want to help shape the future of enterprise AI. We’re hiring across our GTM organization: Marketing • Sales • Partnerships • Federal GTM And across the company in: Engineering • Professional Services • Sales Engineering • EMEA Sales • Internships Whether you’re passionate about building AI-powered products, driving world-class GTM programs, or helping customers succeed, there’s a place for you here. 🔎 Explore all open roles: https://lnkd.in/guyfbdUT If you know someone who would be a great fit, please share or tag them below. Arango | AI Data Platform Help us build Contextual AI — AI that understands your business. #AIcareers #ContextualAI #TechJobs #MarketingJobs #SalesJobs #EngineeringJobs #Partnerships #FederalGTM #ArangoAI #Hiring

AI doesn’t fail because of the model. It fails because of the data underneath it. Most enterprises are learning this the hard way. The moment AI moves from a prototype to a real product, everything that was “good enough” in the data layer starts to break: • Too many systems to integrate • Too many pipelines to maintain • Too many versions of the truth • Too much latency between where data lives and where AI needs it So instead of asking “How do we add more AI?” Leaders are starting to ask: 🟢 “How do we fix the foundation AI depends on?” Forrester just published a new report that hits this head-on: Multimodel Data Platform: The Missing Layer in Your AI Stack. It explains why AI now requires graph + vector + document + transactional context in one place — and why the “polyglot database era” is collapsing under its own weight. It also breaks down the shift we’re seeing across the market: ✅ Enterprises like NVIDIA, Siemens, Synopsys ✅ AI-native builders like Articul8 …are modernizing their data layer before scaling AI — not after it’s already in production. If you’re a CTO, CPO, or engineering leader responsible for delivering AI that’s accurate, explainable, and production-grade, this report is worth your time. 🔗 https://lnkd.in/gAXEEcns Comment if you want the summary version and I’ll DM it. Huge thanks to the authors of this Forrester report — Indranil Bandyopadhyay Oliwia Berdak Noel Y. Aaron Katz, Charlie Dai Nicola (Ostermann) Shorten Francis Harris — for the thoughtful research and clarity in framing this shift.

AI doesn’t fail because of the model. It fails because of the data underneath it. Most enterprises are learning this the hard way. The moment AI moves from a prototype to a real product, everything that was “good enough” in the data layer starts to break: • Too many systems to integrate • Too many pipelines to maintain • Too many versions of the truth • Too much latency between where data lives and where AI needs it So instead of asking “How do we add more AI?” Leaders are starting to ask: 🟢 “How do we fix the foundation AI depends on?” Forrester just published a new report that hits this head-on: Multimodel Data Platform: The Missing Layer in Your AI Stack. It explains why AI now requires graph + vector + document + transactional context in one place — and why the “polyglot database era” is collapsing under its own weight. It also breaks down the shift we’re seeing across the market: ✅ Enterprises like NVIDIA, Siemens, Synopsys ✅ AI-native builders like Articul8 …are modernizing their data layer before scaling AI — not after it’s already in production. If you’re a CTO, CPO, or engineering leader responsible for delivering AI that’s accurate, explainable, and production-grade, this report is worth your time. 🔗 https://lnkd.in/gAXEEcns Comment if you want the summary version and I’ll DM it. Huge thanks to the authors of this Forrester report — Indranil Bandyopadhyay Oliwia Berdak Noel Y. Aaron Katz, Charlie Dai Nicola (Ostermann) Shorten Francis Harris — for the thoughtful research and clarity in framing this shift.

💡 The missing ingredient in Agentic AI “The biggest challenge isn’t the technology—it’s context.” That line from Swami Chandrasekaran, Head of AI and Data Labs at KPMG, in his recent Fortune article says it all. AI agents can only perform as well as the context they understand. Without it, even the smartest “superhuman” agents are running on quicksand. 📊 According to KPMG’s 2025 CEO Outlook, nearly three-quarters of global CEOs plan to invest 20% of their entire budget in AI over the next year—making it their top investment priority for the second year running.   As Swami puts it: “For superhumans and their AI teammates to thrive, enterprises must build robust data foundations and memory systems.” Exactly. Without that foundation, AI can’t capture the meaning, judgment, and intuition that drive real business outcomes. At Arango, we call that foundation the System of Context — the next evolution of AI Data Infrastructure. Unlike traditional data structures that force teams to stitch together multiple databases with brittle pipelines, the System of Context unifies graph, vector, document, key-value, and search data into a single AI Data Layer — preserving relationships and business context so AI can deliver accurate, transparent, and explainable answers that drive better business outcomes. Agentic AI is coming fast. The leaders who act now—by building the right System of Context—won’t just survive this shift, they’ll define it. 👇  Read the full article https://lnkd.in/dTkuCwvx #ContextualAI #AgenticAI #EnterpriseAI #SystemOfContext #Leadership #Fortune

🚀 Context is the missing layer in AI. 🔍 Turning video into insight — powered by context. For leaders managing massive volumes of footage — from security teams to operations and compliance — the challenge isn’t recording video; it’s understanding it. In this NVIDIA Video Search & Summarization (VSS) demo, you’ll see how Arango provides the graph-based context layer that makes intelligent video search possible. By connecting frames, events, and metadata, Arango transforms unstructured video data into contextual knowledge that helps teams detect incidents, understand causes, and act faster. 🎥 Watch the demo → https://okt.to/m09oxK See how context turns raw video into actionable intelligence. 🙌 Thanks to Shubham Agrawal for the demo. #NVIDIA #ArangoDB #ContextualAI #VideoSearch #GraphDatabase #GraphRAG #AIDataPlatform #ComputerVision #EnterpriseAI

We’re excited to unveil the new Arango brand identity, position in the market, website and the Arango AI Data Platform — the trusted data foundation for Contextual AI 🚀 This new chapter truly reflects the people behind it — a team that embodies innovation, collaboration, and relentless curiosity. Big thanks to our amazing teammates:  Shekhar Iyer Ravi Marwaha, Dr. Frank Celler Joshua Shams Mamoona Ajmal Khan Jasmin Weaver Jason Heine Jakki Glivicky Geiger Michael Fonseca Michael Hackstein Heiko Kernbach Max Neunhöffer Anastasia S. Vadim Kondratev Oliver Linares Ryan Coger Anthony Mahanna Ben Quinlan JT Kirtley Arthur Keen, Ph.D. Kimberly Smircich Michael Burleson Anthony Flynn Paula Mihu Tom P. Kaveh Vahedipour and many more who make this journey so special. 🌐 www.arango.ai 📰 Read the launch announcement → https://lnkd.in/gRmgZTnM Here’s to a brand — and a platform — that’s as bold and brilliant as the people behind it. #Arango #AIDataPlatform #ContextualAI #RebrandLaunch #TeamArango #AIInfrastructure #GraphRAG #CelebratingTogether