Drafting funding notices took weeks. Now, a unified database links vector and graph data to generate drafts in five minutes.
An AI startup serving multinational banks and government agencies needed to scale its platform while meeting strict data residency and performance requirements.
To support complex decision-making, the platform needed to ingest and link vector, spatial, and graph data simultaneously. Using separate specialty...
“Autonomous Database 23ai is designed to handle enterprise-scale data volumes and its performance benchmarks reflect the large size of real-world vector workloads.”
Secure AI agents for data unification, compliance, and workflow automation.
Enterprise database software and cloud infrastructure services.
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Manual keyword searches missed hidden funds. AI now matches strategic docs to grants and drafts proposals automatically.
Data scientists spent three months hand-coding models. Automation cut this to hours, pulling the product roadmap forward by a year.
A separate vector DB failed performance benchmarks. Consolidating on one platform scaled daily processing from 200k to 1 billion tokens.
Data policies blocked collaboration. Federated AI detects signals 10x faster, syncing global observatories without exposing raw data.
Drowning in 80,000 monthly alerts, analysts struggled to secure data. AI now prioritizes threats, cutting response time by 99%.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.