Geely is turning connected vehicle data into actionable intelligence via Transwarp's platform. Combining historical and real-time data with AI, the platform supports 300+ vehicle performance indicators and 4 predictive models, with 6–10-minute error in first-departure forecasts.

Spotted in Hong Kong!👀🇭🇰 Transwarp's GPU-Native Cognitive Database is on display at London Plaza, Jordan Road. Built for enterprise Al, it brings 120x faster for demanding analytics workloads. 👉Free trial: tinyurl.com/a8bvaj43 #GPUdatabase #Transwarp #HongKong

📈As AI workloads grow, model compute is only part of the equation. Large scans and complex joins can strain the data layer. Transwarp Cognitive Database brings GPU-native processing to SQL analytics, helping teams accelerate demanding queries and turn data into insights faster.

🥇Real business value from AI depends on turning enterprise data into timely insights and action. Built on a fully GPU-native architecture, Transwarp GPU-Native Cognitive Database delivers high-performance, low-latency analytics for data-intensive AI applications at scale.

🤔What if data governance were as simple as a conversation? Built on Transwarp Data Studio, Astro is an AI-powered data governance agent that turns natural-language requests into workflows for data quality, security, standardization, and lineage analysis—no coding required.

🔎Find how fuel transactions reveal customer insights. Transwarp Big Data Platform turns CNPC retail data into real-time insights and targeted marketing. It linked 16M+ transactions and generated 1M+ card recommendations, contributing to a 39.38% card enrollment conversion rate.

🤔How is Lenovo turning siloed data into smarter software diagnosis? With Transwarp Sophon LLMOps, Lenovo built a knowledge graph-driven platform supporting 100+ diagnostic sub-scenarios and 70+ tool and log types, with ≤2s early risk warnings and 99.5%+ platform availability.

🔎How is SPD Bank scaling enterprise AI with Transwarp Sophon LLMOps? By turning scattered data and documents into governed, reusable knowledge assets, the bank achieved 5× higher knowledge production efficiency, 80% less manual effort, and deployed 100+ AI Agents.

🤔AI adoption is accelerating, but data readiness remains a challenge. Scaling enterprise AI requires more than smarter models. It demands reliable, high-quality data, timely, secure access, and infrastructure that performs at scale. Better data infrastructure powers better AI.