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GraphAI DevLog 8 - Scaling for the Agentic Future Faster Queries, Smarter Onchain Logic, AI-Ready Performance This week we rolled out upgrades focused on speed, precision, and reliability. ✅ Flag Response – users can now flag incorrect AI outputs, creating a feedback loop to

Our team is development-first and always looking for ways to make GraphEngine faster and more efficient. This week we cut query latency by over 7 seconds. By deploying a Neo4j read-only replica, heavy reads no longer slow down writes. And by shifting lighter tasks like summaries

If you signed up for the GraphEngine Closed Beta, you should have received an email with your unique authorization code. Here’s our Head AI Scientist Akhil, walking you through the login process step-by-step so you can start testing subgraph querying in real time. If you've not

GraphAI is becoming the connective tissue between live on-chain data, AI reasoning, and actionable insights. From L1 integrations and tokenized asset coverage to enterprise-ready private subgraphs and hybrid off-chain datasets, our growing integration ecosystem is enriching

We’ve rolled out a powerful new feature in the GraphEngine Beta app. Testers can now flag and comment on any inaccuracies in query outputs directly inside the app. This streamlined feedback loop ensures the GraphAI dev team can identify and fix bugs fast, improving accuracy and