Chemists waited minutes to query 100M+ reactions. A vector engine returns matches in seconds, enabling real-time drug design.
A pharmaceutical technology company optimizes drug discovery by analyzing databases containing hundreds of millions of chemical reaction records.
Chemists needed to rapidly explore synthetic pathways using high-dimensional molecular data, but traditional databases lacked the indexing...
Carbon nanotube-based quantum processors for high-fidelity quantum computing.
Vector database platform for building and scaling AI applications.
Related implementations across industries and use cases
Legacy tools choked on billions of records. A central vector store now unifies fragmented apps for 5x faster, context-aware search.
Searching billion-document archives took 30 seconds. AI now retrieves data instantly and drafts regulatory submissions.
Predicting a single protein binding took 2,000 hours. Deep learning models now complete the task in just 15 minutes.
Query spikes choked the old matcher. Zilliz Cloud cut latency to 50ms for 2M daily searches, enabling growth to 100k users.
Daily updates left stock data lagging. Real-time indexing now syncs inventory instantly, ensuring exact matches for specific part numbers.
Complex tables in 100-page docs bottlenecked teams. AI now parses text and images, ensuring every output is traceable and compliant.
Manual workflows delayed global campaigns for weeks. Now, local teams use GenAI to instantly draft localized, regulatory-compliant copy.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Custom hardware bottlenecked imaging. A switch to software-defined GPUs now renders photorealistic 3D hearts in real time.