Watch this 60-second video to see how Data Graphs can transform scattered knowledge into structured intelligence. Ask questions of your business information using AI, without compromising your data security. Get in touch here for a demo! datagraphs.com/request-a-dem…

Food is currently exempted from the EU Digital Product Passport #DPP regulation, but the wider compliance landscape is moving fast. Batteries lead the timeline in February 2027. Textiles, iron and steel, and tires follow throughout 2027 and 2028. Furniture, aluminum, and consumer goods extend into 2030. Meanwhile, CSRD requires structured sustainability reporting. EUDR requires due diligence on commodity origin. Plant protection products are themselves regulated, and data about them is increasingly expected to flow downstream. For food and retail, the challenge is the same: resolving a GTIN on the shelf back to the batch, the ingredients, the farms, and the inputs behind it. Data Graphs delivers a @gs1 -aligned Digital Product Passport foundation built for that work. Come talk food and retail data with us at GS1 Excellence Day 2026 on June 18 in Zurich.

From February 18, 2027, every industrial battery above 2 kWh placed on the EU market must carry a Digital Product Passport #DPP covering composition, carbon footprint, state of health, and recycled content. The data already exists across PLM, ERP, MES, and supplier systems. The challenge is connecting representations of the same product across systems with different identifiers, structures, and semantics. A GS1-aligned data foundation resolves that fragmentation and enables a coherent lifecycle record to be queried on demand. See it in action at @gs1 Switzerland Excellence Day 2026 in Zurich on June 18.

Proud to be a @gs1 Switzerland Solution Partner. GS1 standards make Digital Product Passports work at scale. Globally recognized, interoperable data from product identification to consumer delivery, for manufacturers of every size. We’ll be at GS1 Switzerland Excellence Day 2026 in Zurich on June 18. If #DPPs are on your roadmap, let’s connect in person.

Digital Product Passports are about to redefine what "knowing your product" means. On June 18, Data Graphs will be at @gs1 Switzerland Excellence Day 2026 in Zürich to show how DPP becomes a strategic asset, not just a compliance project. Are you scoping DPP for energy-related products, batteries, food, textiles or iron and steel? Come find us.

Why deep graph traversal breaks most engines. How Data Graphs runs deep queries orders of magnitude faster than Neo4j, in a fraction of the memory, and with higher throughput datagraphs.com/blog/beyond-t…

Most "Graph RAG" implementations are vector retrieval with extra steps. @datagraphs built something different. Their UK-based knowledge graph platform combines a proprietary graph database engine with Qdrant-powered semantic search, orchestrated by an agentic layer that picks the right retrieval path for each prompt. The insight from CEO Paul Wilton: vector and graph aren't competitors. They're complementary. Vector excels at semantic similarity over unstructured content. Graphs excel at empirical queries: negation, date ranges, mathematical operations on connected data. Force one to do the other's job and the system breaks. What they built: - Real-time embedding from the graph into Qdrant collections via streaming and queuing - Schema-first retrieval where the agent pulls the full graph schema before deciding how to query - Parallel execution across graph queries and vector retrieval, blended for the LLM - Every answer cited back to source for verifiable provenance Why Qdrant specifically: - Hybrid Cloud kept the entire stack inside their own AWS environment - Payload filtering DSL closely matched their existing OpenSearch patterns, so common metadata structures worked across the graph, OpenSearch, and Qdrant without translation - Terraform support and infrastructure automation fit their existing CI/CD workflows 18 months in production. Zero significant issues. The retrieval layer determines the ceiling of your AI's intelligence. Choose the right components. Compose them well. Full case study: qdrant.tech/blog/case-study-…

Last week at the @HowieLongShort Spring Huddle, Burke Magnus, Andrew Yaffe, and Alex Michael had a thoughtful conversation about where sports and media are heading. AI is reshaping how content reaches fans. But it opens a different problem around context, ownership, and commercial intelligence. That gap is what the industry needs to talk about next. Data Graphs exists because of this problem. Book a demo and see it in action.

Context wins. Not more data. Not another dashboard. Not higher reach. Context. When AI actually understands your business - the relationships between your content, your fans, your sponsorships, your rights - everything shifts. → Sponsorship becomes provable. → Fan experiences become personal. → Media becomes reusable. Our CRO, Donna Esfandiary, is speaking at the invitation-only JohnWallStreet Spring Sports & Media Huddle on April 22nd in NYC - alongside some of the sharpest minds in sports and media: - Burke Magnus, President of Content at @espn - Andrew Yaffe, CEO of @DudePerfect - Alex Michael, Managing Director at LionTree If you're in the room, come find us. If you're not - let's talk anyway. #JohnWallStreet #SportsBusiness

A new chapter for Data Graphs. Our new website is live! datagraphs.com A clearer view of what we build and why it matters. Context Wins.

Vector search finds what's similar, Knowledge Graphs find what's true. The most powerful private-data AI systems know when to use each. Read why > datagraphs.com/blog/vector-f…

See how our AI-powered multi-modal knowledge graph can unlock the full value of sports media by unifying video, sports data, and Agentic AI within a single semantic framework. Using the IPTC Sports Schema and real Premier League and Champions League footage, it shows how structured sports data, AI video analysis, true hybrid GraphRAG, and contextual rendered views transform raw match footage into an intelligent, explorable knowledge hub. The result is faster analysis, richer storytelling, deeper fan engagement, and more powerful performance and editorial workflows across any sport. datagraphs.com/blog/how-mult…

💥 𝗨𝗻𝗹𝗼𝗰𝗸𝗶𝗻𝗴 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝘄𝗶𝘁𝗵 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗚𝗿𝗮𝗽𝗵𝘀 If you want to scale your organization’s knowledge with Agentic AI, the killer feature is a cohesive, well-defined knowledge graph schema. datagraphs.com/blog/what-mak…

Join Data Graphs for a discussion of the @IPTC Sports Schema—developed with key contributions from our team—tomorrow, Thursday, May 15, at the IPTC Spring Meeting 2025 in Juan-les-Pins, in the south of France! @pwilton , Donna Esfandiary, and Silver Oliver will showcase Data Graphs for sports utilizing IPTC standards: a football content graph enriched with action metadata and powered by our GraphRAG AI. See you there!

claude one-shot a UI around a suite of cypher query perf tests - its great for building stuff like this. It highlighted the comparison with "OtherDB" (industry leading graph db that we measure against 😉) ... made me laugh so i made myself a motivational poster 🏋️‍♂️