kdb.ai: Powering Real-Time, Explainable AI with Scalable Vector Search

kdb.ai is a cutting-edge, scalable vector database engineered for advanced contextual and time-series search, enabling developers and organizations to build real-time, explainable AI systems with unparalleled speed and accuracy. Designed by KX, it excels in handling both structured and unstructured data—including text, video, audio, images, telemetry, and logs—through multimodal Retrieval Augmented Generation (RAG), hybrid search, metadata filtering, and temporal similarity search (TSS). With support for high-performance indexing methods like HNSW, IVFPQ, and qFlat, kdb.ai delivers sub-second latency across billions of data points, while features such as Zero Embedding search and Killer Compression drastically reduce memory usage and accelerate performance for dynamic and static datasets alike. Its robust capabilities extend to financial AI applications, including personalized portfolio management, real-time alpha/beta extraction, anomaly detection, and market regime shift identification, all backed by full audit trails, citations, and transparent reasoning. The platform supports flexible deployment—on-premises or across any cloud provider—and offers unlimited memory, storage, and query capacity. With free trial access and comprehensive onboarding resources including documentation, a Learning Hub, and GitHub tutorials, kdb.ai empowers teams to rapidly prototype and deploy intelligent systems. Whether for finance, research, or enterprise AI, kdb.ai stands out as a future-ready foundation for data-driven decision-making.

Key Features:

• Scalable vector database for contextual and time-series search
• Hybrid search combining similarity, exact, and literal queries in one operation
• Multimodal RAG support for text, video, audio, images, telemetry, and logs
• Temporal Similarity Search (TSS) and Time-Series Clustering (TSC) for dynamic data
• Zero Embedding search for 17x faster query performance and 12x lower memory usage
• Killer Compression reducing memory and storage by 100x with 10x faster search
• On-disk indexing via qHNSW and qFlat for cost-efficient scalability
• Sub-second latency similarity search across billions of rows
• Real-time monitoring of client profiles, portfolios, and market data
• Automated portfolio rebalancing based on risk and exposure drift
• AI personalization with embedded client preferences, ESG mandates, and risk policies
• Explainable AI with full audit trails, visual context, and rationale
• Multi-source insights with verifiable citations
• Signal detection across multiple assets and timeframes
• Alert and action triggering based on image and sensor data
• Integration with leading Gen AI tools
• Flexible deployment: on-premises or cloud provider of choice
• Unlimited memory, storage, reads/writes, tables, and indexes
• Free trial and onboarding resources (docs, Learning Hub, GitHub tutorials)

Pricing: kdb.ai offers a 90-day free trial with no upfront cost, making it ideal for evaluating its capabilities before committing. After the trial, pricing is available through a custom enterprise model, typically via sales consultation.

Conclusion: With its powerful combination of real-time performance, multimodal data handling, and explainable AI, kdb.ai is a transformative tool for developers and enterprises building intelligent, scalable applications—especially in finance, research, and complex data environments.