Ekolabs AI
Ekolabs AI builds secure, private AI infrastructure for enterprises, combining dedicated engineering teams with proprietary compute ownership. The company operates its own Private AI Cluster built on NVIDIA DGX Spark™ hardware, enabling clients to avoid rented APIs and maintain control over data and model performance. Their platform delivery spans architecture, AI/ML pipeline development, and DevOps, with one system processing 10,000+ organizations.
- Artificial Intelligence
- Software Only
- AI Agents
- Developer Tools
- Enterprise Software
Funding
Founders
Founder details are not available yet.
Product
Problem
Enterprises in high-stakes industries often struggle to build AI systems that meet stringent security, privacy, and performance requirements when relying on public cloud infrastructure and rented APIs. Limited internal engineering capacity, fragmented architecture, and insufficient compute ownership can stall AI initiatives and leave organizations exposed to data governance and latency risks.
Solution
Ekolabs AI builds secure, private, and high-performance AI infrastructure for AI-native enterprises, combining dedicated engineering teams with proprietary compute ownership. The company operates its own Private AI Cluster built on NVIDIA DGX Spark™ hardware, enabling clients to avoid dependency on rented APIs and maintain control over data and model performance. Ekolabs embeds cross-functional teams covering architecture, full-stack development, AI/ML, DevOps, and QA to deliver end-to-end platform development. Their approach prioritizes reproducible local environments with Docker and Kubernetes parity, ensuring consistent deployments across staging and production for mission-critical AI workloads.
Target Audience
Primary customers are B2B SaaS companies and high-stakes industry enterprises—such as those in competitive intelligence, value selling, and similar data-intensive verticals—that need secure, custom-built AI platforms without an in-house engineering team.
Features
- Private AI Cluster powered by 4x NVIDIA DGX Spark™ nodes, enabling self-owned compute for AI workloads without public cloud dependency
- Centrally provisioned high-performance workstations with full-disk encryption and standardized development tooling for security compliance
- Reproducible Docker and Kubernetes environments ensuring parity between local, staging, and production deployments
- End-to-end platform delivery covering system architecture, AI/ML pipeline development, and DevOps/QA, as demonstrated by a platform processing 10,000+ organizations
- LLM-driven classification and proprietary scoring engines, achieving over 80% classification accuracy in production
- Joint patent development capability, including a filed U.S. Provisional Patent Application (No. 63/888,831) for AI-powered competitive intelligence methods