Build high-performance cybersecurity applications
Spice provides the data and AI foundation for modern security solutions-combining federated access, acceleration, and resilience for low-latency, high-trust systems.
Do more with your data
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up to 100x faster queries
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up to 80% cost savings on data lakehouse spend
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increase in data reliability for critical workloads
Security apps demand more from their data layer
Security platforms rely on constant streams of telemetry, logs, and threat data. Traditional databases and pipelines introduce latency, complexity, and cost. These systems struggle to maintain performance under heavy workloads or network failures. Developers need a unified, resilient data runtime to power AI-driven insights and real-time analysis without operational friction.
A query engine built for secure, high-scale workloads
Unify, accelerate, and govern your data for reliable, low-latency operations.
Low-latency data acceleration
Spice materializes frequently accessed data close to your application for instant reads, faster analytics, and predictable performance.
Resilient and distributed
Run Spice at the edge, in the cloud, or in hybrid deployments to maintain continuous access even during network disruptions or provider outages.
Unified data access
Query data across logs, object storage, and analytical systems in real time. Simplify architecture and remove complex ingestion and transformation pipelines.
AI-ready and auditable
Integrate LLMs and vector search directly within the runtime for intelligent detection, triage, or reporting. Every query and inference is traceable and governed.
The data and AI runtime for modern security applications.
Spice powers fast, resilient, and intelligent security applications with unified access, built-in acceleration, and enterprise-grade governance.
Enterprise-Grade Performance
Query and serve results in milliseconds for real-time detection and response.
Resilience at Scale
Edge and distributed deployments ensure uptime even under adverse conditions.
Modern SQL Federation
Federate data from object stores, warehouses, and databases with zero ETL.
Governed and Secure
Native authentication, encryption, and audit logging built into every query.
AI-Enabled Insights
Built-in hybrid search and inference capabilities for contextual analysis.
Deployment Flexibility
Deploy Spice as a sidecar, cluster, or managed service, wherever your app runs.
Deployed in production
Run data-intensive workloads on a high-performance engine trusted by teams building real-time systems at scale.
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Faster queries
“It just spins up and works, which is really nice. The responsiveness is amazing, which is a huge gain for the customer.”
Darin Douglass
Principal Software Engineer, Barracuda
“Spice opened the door to take these critical control-plane datasets and move them next to our services in the runtime path.”
Peter Janovsky
Software Architect, Twilio
“Partnering with Spice AI has transformed how NRC Health delivers AI-driven insights. By unifying siloed data across systems, we accelerated AI feature development, reducing time-to-market from months to weeks - and sometimes days. With predictable costs and faster innovation, Spice isn't just solving some of our data and AI challenges - it's helping us redefine personalized healthcare.”
Tim Ottersburg
VP of Technology, NRC Health
Trusted by global enterprises
Build more scalable security apps
Guides and examples to learn more about building with Spice.
Intelligent Security Copilot Cookbook
Follow this step-by-step recipe to stream query logs into Spice, apply AI-driven pattern analysis, and surface alerts for suspicious database activity.
Data Retention Policy Cookbook
This recipe shows how to set up a retention policy for an accelerated dataset to evict data older than a specified duration.
Documentation
Explore the docs for examples, additional cookbooks, starting templates, and more.
FAQs
Common questions about using Spice.ai in cybersecurity applications
How do cybersecurity companies use Spice.ai?
Cybersecurity companies use Spice.ai to unify telemetry, logs, and threat data behind a single query engine and serve it to detection and response applications at low latency. The runtime federates data from object stores, warehouses, and databases with zero ETL, and materializes frequently accessed data close to the application for predictable performance under heavy workloads.
Can Spice.ai query security logs stored in object storage?
Yes. Spice.ai queries logs and events in object storage with standard SQL and joins them with data in warehouses and databases in real time. With data lake acceleration, frequently accessed datasets are materialized locally for instant reads and faster analytics, without complex ingestion or transformation pipelines.
How does Spice.ai keep security applications available during outages?
Spice.ai runs at the edge, in the cloud, or in hybrid deployments, so security applications maintain continuous data access during network disruptions or provider outages. Locally accelerated copies of critical datasets keep reads fast and available even when upstream systems are unreachable.
Does Spice.ai support AI-assisted threat detection and triage?
Yes. LLMs and vector search run directly within the Spice runtime, so security applications can add intelligent detection, triage, and reporting without operating a separate AI stack. Every query and inference is traceable and governed, which supports audit requirements for automated analysis.
What security controls does Spice.ai itself provide?
Spice.ai builds native authentication, encryption, and audit logging into every query, and Spice AI maintains SOC 2 Type II compliance. See the Spice AI security and compliance practices for details on access controls, encryption, and secure development.
See Spice in action
Walk through your use case with an engineer and see how Spice handles federation, acceleration, and AI integration for production workloads.
Talk to an engineer