Dive into @GraphAIOfficial GraphGrid GraphGrid turns GraphAI’s data storage layer into a community-owned, reward-generating infrastructure network — where anyone can stake and earn from the data that powers decentralized AI. How it works: Every subgraph and dataset on GraphAI needs to be stored somewhere. GraphGrid decentralizes this storage, letting users own or stake units of data infrastructure, like holding a share in the network itself. When the data is used or accessed, those nodes earn rewards. Staking helps secure the system, while giving holders a real stake in its economics. Next level tech fr

2/ GraphRWA: this is the RWA layer that adds compliance and management to tokenized assets for easy integration and discovery 3/ GraphFi: this is the intelligence layer it turns blockchain feeds into live insights for DeFAI trading, lending, and governance 4/ GraphGrid: this product links data to physical infrastructures (DePIN) it turns data ownership into something stakable, rewarding people who contribute

4. GraphGrid: This product links data to physical infrastructures (DePIN). It turns data ownership into something stakable, rewarding people who contribute.

Happy Thursday to everyone! Do you remember when I told you that I'm enjoying Base Chain more and more these days? Yep, still doing that. Kanye is destroying the Sol one with his token, we can't find any utility projects that can actually last another 100 reasons... For example, @GraphAIOfficial has launched only one month ago and they didn't let success take over their project, instead, they kept building more and more. Let's see what Graph is about and why you should put it on your watch list. A thread🧵 Content: 1⃣ Introduction 2⃣ The Problem GraphAI Solves 3⃣ The GraphAI Solution ↶ ↷ ↶ ↷ ↶ ↷ ↶ ↷ 1⃣ Introduction I think that a new era of DeFAI is here. Meet the first AI-powered data infrastructure built on MCP and fueled by GraphRAG tech. It's designed to seamlessly connect RWAs with on-chain DeFi systems. - DeFAI: where AI meets decentralized finance - RWAs: set to reach $30T by 2030, now entering the on-chain space - Autonomous, AI-driven strategies now possible on-chain How is going GraphAI to transform how blockchain data is used? It's not very hard to understand, just pay attention. - Combines historical live blockchain data - Builds intelligent knowledge graphs - Enables scalable AI dApps with real-time insights By extending LLM capabilities with deep, contextual blockchain knowledge, GraphAI is laying the foundation for smarter Web3 apps. Smarter Web3 apps? Yea, you heard it right. 2⃣ The Problem GraphAI Solves People often see problems that repeat everyday, don't have a solving yet, creating problems to them and to other people and still decide to do nothing. They don't even share it around so other people can take care of it. The rise of AI in DeFi has sparked a new frontier: DeFAI, where autonomous agents run sophisticated strategies with little human input. But there’s a catch… Until Real World Assets are fully integrated into these systems, DeFAI will stay on the sidelines of mainstream finance. What’s holding it back? - Disorganized Data - Poor RWA Compatibility - On-chain data lacks depth This data gap leaves builders and traders stuck with manual work and make analytics disappear like they weren't even there. Shorter, it's blocking the real fusion of AI, DeFi, and RWAs. The future of DeFAI depends on smarter, cleaner, and more connected data. 3⃣ The GraphAI Solution GraphAI is redefining the data layer for DeFAI. Why do I say this? It’s the first AI-powered system built from the ground up to connect RWAs with autonomous on-chain finance. Here’s how it’s unlocking the next generation of DeFAI protocols 👇 a) GraphAI transforms messy, scattered blockchain data into structured intelligence. b) GraphAI’s custom indexes and API-ready structure let AI agents pull exactly what they need. c) GraphAI builds deep relational maps of on-chain activity. What makes it different? GraphAI was designed specifically for RWA integration—something no other solution offers today. Its core stack includes: 🔹 GraphEngine – Knowledge graphs for real AI comprehension 🔹 GraphRWA – Compliance discovery layer for tokenized assets 🔹 GraphFi – Real-time intelligence for DeFi strategies 🔹 GraphGrid – A decentralized data layer for DePIN and staking GraphAI is the backbone for scaling DeFAI into the real world. It doesn't matter you trading solo, an institutional player or something else, GraphAI is here for you. But... can you accept it into your life? Personally, I would. If we don't make a change now we will still live like 10 years ago another 10 years from now. So, it's your choice😆 Share your thoughts in the comments and don't forget to repost and to follow @Shuarix for more reading stuff.

Blockchain and AI are two of the most powerful inventions in mankind. ​ Innovation is through the roof, yet the two don't communicate well with one another. ​ What we've seen so far is nothing compared to what will happen when these two communicate properly. ​ @GraphAIOfficial is bringing this solution right now! 📃👇 So, what is GraphAI? ​ TLDR: Graph is the first MCP-based, GraphRAG-powered AI data layer enabling the integration of RWAs into the world of DeFAI. ​ Graph is solving a few issues developers are facing as we start to automate financial processes using AI, starting with four core products: ​ 🔹 GraphEngine, knowledge graphs to better map blockchain data. 🔹 GraphRWA, compliance, and management protocol for RWAs. 🔹 GraphFi, real-time intelligence protocol for everything financial. 🔹 GraphGrid, a decentralized data ownership and staking protocol for DePIN ecosystems. ​ Their goal is simple: to empower developers and users with the tools necessary to create personalized, AI-ready datasets from blockchain data, enabling developers to build a new era of AI and LLM-powered dApps. ​ For those who haven't heard about Model Context Protocol (MCP) yet, see it as the USB of AI. Instead of needing endless tools that don't work together, MCP is the one-size-fits-all solution to make AI far more efficient. ​ It's a core component that will likely supercharge the development of future AI tools. ​ The GraphAI workflow consists of several key stages: ​ 1️⃣ Data Ingestion: Continuous indexing of blockchain data (node providers). 2️⃣ Sub-Index Creation: User-defined creation of specialized data subsets. 3️⃣ Vector Database Storage: Efficient storage of sub-indexes for AI operations. 4️⃣ Knowledge Graph Integration: Mapping relationships and context within the data. 5️⃣ MCP Access: Enabling developers to query and utilize the processed data. 6️⃣ AI/LLM Application Development: Creation of intelligent dApps leveraging GraphAI's capabilities. ​ Graph is backed by an incredibly skilled team, with members having worked at Google, JPMorgan Chase, and the former CTO of Vanvar. ​ They have a strong marketing lead which is essential for Graph to expand their reach. As a B2B company, their number one goal will be to expand their reach and get companies to adopt their tech. $GAI tokenomics are super favorable, only 1% of tokens were sold to the public, with 69% allocated to the LP for a fair launch. ​ The remaining 30% has been reserved for grants, curators, and node providers, each getting 5%, 12.5%, and 12.5% respectively. ​ $GAI unlocks premium GraphAI features like advanced data indexing, live sub-index creation, and AI-optimized querying. Developers and enterprises use $GAI to interact with knowledge graphs and MCP. ​ Additionally, $GAI is used to reward node providers, which are needed to provide real-time blockchain data access to all who are using Graph's services. Initially, after some FUD around the fair launch, it is currently trading around a $15M market cap and IMO an interesting bet on RWAxAI. ​ I hope you enjoyed this post 🫡 ​ These posts take a long time, so I'd appreciate it if you could like and retweet it.

At GraphGrid, we believe that AI augmentation is a core necessity to help you succeed in the future. @bennussbaum explains why we've systematically introduced AI augmentation as a native component of GraphGrid CDP. bit.ly/3JuTWtI #KnowledgeGraphs #GraphDatabase

Learn how @GraphGrid Showmes allow your dev team to push out dynamic #APIs to non-technical users that give everyone the power of #connecteddata insights, in this blog post by Mike Ulring. graphgrid.com/blog/showmes-1… #Geequel

GraphGrid CTO @bennussbaum describing the Knowledge Graph Driven AI System that will be at the core of the CDP 2.0 AI Edition. #GraphGridConference2021

@AmpHuman @chromaway @fraym_io @graphgrid @haasalert @HashiCorp @hyasinc @HyprCorp @VerifiedbyAI @Infinite_C_T @IonChannel_io @KeplerComms @lynq_me @NuCypher @OutSystems @panaseer @Phylum_IO @privitarglobal @RBCSignals

One-Point Room Perspective Grid for Interior Designers: Add a New Dimension to 3D Hand Sketches with Perspective Grid Journals buff.ly/39nKp6J #journal #sketchbook #interiordesigner #perspectivegrid #onepointperspective #graphgrid

You can use @GrapheneDB or @graphgrid

@graphgrid @GrapheneDB are 2. I believe they both host open source Neo4j core and ONgDB (Neo4j core enterprise code removed by Neo last year.).

Check out @graphgrid as well - they provide production support for open source licensed distros /forks of Neo4j including ONgDB. I think their pricing is listed on their website.

Sponsored presentations w/ @XTIVIA, @denodo, @graphgrid, @ontotext, @TopQuadrant, and @PoolParty_Team starting in 15 minutes! Today's full schedule here: ow.ly/bbNj50wLPSU #DASummit #Graphorum

We're at #AFWERXFusion19 & excited to see some of our incredible #DcodeAlumni tech companies! @Trifacta @cryptomove @thoughtspot @chromaway @DataRobot @graphgrid @Hivemapper @OmniSci @sling_shot_aero @streamsets @virtruprivacy @myWickr

Check out #GraphGrid. It is on AWS and pricing is very reasonable from what I have seen.

@bradnussbaum Need urgent help with graphgrid production instance down. Can you please help?

From the archives: GraphGrid: A Secure Global #ConnectedData Platform r.neo4j.com/2xOfn8m via @bennussbaum @graphgrid

From the archives: GraphGrid: A Secure Global #ConnectedData Platform r.neo4j.com/2kWMjFW via @bennussbaum @graphgrid

Also if you need managed #neo4j in any region in #AWS you should give @graphgrid a try at go.graphgrid.com - if you need any help with it we can get you setup with an instnace