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Nava

Nava provides an AI factory platform with purpose-built infrastructure for building, serving, and operating AI systems at scale. The platform integrates parallel file systems, a unified data lakehouse, vector databases, and a centralized model registry to streamline machine reasoning workloads. It targets engineering and data teams at enterprises and AI-native companies needing production-grade AI infrastructure.

Traction 9/10
Singapore, Singapore · HQ
Founded 20257220K+ followers
  • Artificial Intelligence
  • Developer Tools
  • Software Only
Updated 5 days ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Organizations building AI systems often struggle with infrastructure that is not designed for machine reasoning workloads. General-purpose cloud services lack the data throughput, storage efficiency, and model lifecycle management needed to operate AI at scale, forcing teams to assemble fragmented tools and manage performance bottlenecks.

Solution

Nava delivers an AI factory platform with everything needed to build, serve, and operate AI on purpose-built infrastructure. It provides parallel file systems for distributed, high-throughput storage across compute nodes, a unified data lakehouse combining raw storage with ACID-compliant tables and query execution, and vector databases engineered for low latency retrieval. The platform also includes a centralized model registry to version, track, and manage model artifacts across development and production environments. By unifying these components, Nava aims to simplify the operational complexity of running AI workloads.

Target Audience

Primary customers are engineering and data teams at enterprises and AI-native companies that need production-grade infrastructure to build, serve, and operate AI systems at scale.

Features

  • Parallel file systems designed for large datasets and concurrent access across compute nodes
  • Data lakehouse platform unifying raw storage, ACID-compliant tables, and query execution in a single system
  • Vector databases engineered for low-latency retrieval in AI applications
  • Centralized model registry for versioning, tracking, and managing model artifacts across environments
  • Infrastructure purpose-built for machine reasoning and autonomous AI operations
This profile is AI-generated and may contain inaccuracies.