Twelve Seed-stage companies building the data infrastructure, security platforms, and AI systems defining the intelligence era.
Zero-trust identity and secrets management platform for cloud-native enterprise environments. Prevents lateral movement and credential compromise across hybrid deployments.
AI-driven threat detection and correlation engine for SOC teams. Reduces alert fatigue by 80% while increasing true positive detection rates through behavioral baseline analytics.
Continuous software supply chain monitoring and SBOM management for enterprises. Detects compromised dependencies before they reach production through ML-based anomaly analysis.
Cloud configuration drift detection and automated remediation platform. Ensures infrastructure-as-code compliance and prevents security misconfigurations across multi-cloud deployments.
Intelligent data pipeline orchestration with built-in observability, lineage tracking, and anomaly detection. Trusted by Fortune 500 data engineering teams managing petabyte-scale workloads.
Automated data quality validation and contract enforcement platform. Detects and quarantines bad data before it reaches downstream consumers, models, or dashboards.
Active data catalog with automated classification, lineage propagation, and policy enforcement. Turns passive metadata repositories into operational governance infrastructure.
Unified streaming analytics platform bridging Apache Flink and the modern data lakehouse. Enables sub-second latency analytics on event streams without separate infrastructure stacks.
Production-grade vector database and retrieval infrastructure for enterprise LLM applications. Handles billion-scale embeddings with millisecond retrieval latency and enterprise access controls.
End-to-end MLOps platform for model versioning, deployment, monitoring, and governance. Provides the operational infrastructure that separates production AI from notebook experiments.
Inference optimization and serving infrastructure for enterprise LLM deployments. Reduces inference cost by up to 70% through dynamic quantization, speculative decoding, and intelligent caching.
LLM observability and evaluation platform tracking prompt performance, output quality, cost, and safety across production AI deployments. The missing operational layer for enterprise AI applications.
We are actively deploying capital into Seed-stage companies in data technology, cybersecurity, and AI infrastructure. If you are building in these spaces, reach out.
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