PaleBlueDot AI, Inc.
Aggregates global GPU clusters to provide low-latency, secure, and cost-efficient computing for AI model deployment and scaling via an AI Cloud Agent platform.
At a Glance
- AI Startups
- Enterprise AI Teams
- Large-scale AI Model Developers
- Regulated Industries requiring private cloud
AI Tools by PaleBlueDot AI, Inc.
(1)PaleBlueDot AI
Global AI GPU Cluster Platform
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Latest News
PaleBlueDot AI Raises $150M Series B to Scale Global AI Compute Infrastructure
PaleBlueDot AI Unveils Dot-1.1: The First AI Cloud Agent Powering Next-Gen AI Computing
Vincent Li Joins PaleBlueDot AI as Chief Financial Officer
PaleBlueDot AI Surpasses $2M ARR with 10x Growth
Products & Services
An AI Cloud Agent designed to streamline AI model deployment and reduce inference costs with a real-time GPU pricing engine.
A unified API access layer providing connectivity to multiple AI models (OpenAI, Anthropic, DeepSeek, etc.) via a single base URL.
Enterprise-grade reserved GPU clusters for custom compute solutions and large-scale deployments.
Market Position
Positioned as a 'neocloud' leader, offering a more flexible and cost-effective alternative to hyperscalers by aggregating global GPU clusters and using an AI agent (Dot) to optimize compute resources.
Leadership
Founders
Jonathan Zhu
CEO and Founder. Stanford University Graduate School of Business alumnus.
Shaodong Huang
Co-founder.
Sheldon Ng
Co-founder. Background in start-up leadership and venture capital.
Executive Team
Jonathan Zhu
Chief Executive Officer & Founder
Stanford GSB graduate, led the company through $200M+ in funding rounds.
Vincent Li
Chief Financial Officer
Joined in June 2025. Previously VP of TMT Investment Banking at J.P. Morgan and Analyst at BofA Merrill Lynch.
Board of Directors
Founding Story
Founded in 2024 by Jonathan Zhu, Shaodong Huang, and Sheldon Ng, the company was started to address the critical need for scalable and cost-effective AI compute infrastructure. The founders envisioned a 'neocloud' that could aggregate global GPU resources to solve the fragmentation and high costs of AI model deployment.
Business Model
Revenue Model
Usage-based pricing for API access (TokenRouter) and subscription/reserved capacity pricing for GPU clusters (Token Factory).
Pricing Tiers
Real-time pricing based on GPU model, region, and deployment size.
Reserved GPU infrastructure for large-scale custom compute.
Target Markets
- AI Startups
- Enterprise AI Teams
- Large-scale AI Model Developers
- Regulated Industries requiring private cloud
- Scalable AI model deployment
- Inference cost reduction
- Enterprise AI infrastructure scaling
- Secure private cloud AI compute for sensitive workloads
- Enterprise demand from global AI companies
- RedNote