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Autopiloting your AI infrastructure

Chamber puts your AI infrastructure on autopilot. Our agentic AI enabled platform orchestrates, governs, and optimizes your AI infrastructure so teams can run ~50% more workloads on the same GPUs without manual intervention. It operates like an autonomous infrastructure team: continuously monitoring GPU clusters, forecasting demand, detecting unhealthy nodes, and reallocating resources in real time to where they create the most impact. Your ML teams move faster, infra waste drops, and GPU bottlenecks disappear.
Active Founders
Charles Ding
Charles Ding
Founder & CEO
Second Time Founder with 1X Exit | Former Engineering Leader at Meta & Amazon | Ex-Microsoft. We are building to accelerate the world’s AI innovation through efficiency.
Andreas Bloomquist
Andreas Bloomquist
Founder
I have a passion for distilling complex problems into elegant simple solutions for customers. Ex-Aamzon Product Manger with experience delivering observability and GPU efficiency solutions. I also have a passion for technical selling and GTM strategies. From my experience both Optimizely and Amazon, I am a believe in the power of experimentation to iterate quickly and deliver results.
Jason Ong
Jason Ong
Founder
I’m a software engineer from Malaysia who moved to the U.S. in 2016. I’ve built high-impact systems at Amount, Avant, Flexport, and Amazon. I’ve worked across fintech, logistics, and GPU-related scheduling tooling, where I saw how hard distributed training is for many teams. I’m now co-founder of Chamber, focused on simplifying GPU orchestration for training workloads.
Shaocheng Wang
Shaocheng Wang
Founder
I am a cofounder of Chamber and a former Senior Software Engineer at Amazon. Over the past 9+ years, I’ve built and launched multiple 0→1 AWS products, with deep expertise in large-scale observability, distributed systems, and AI infrastructure efficiency. At Chamber, I’m applying this experience to build intelligent AI workload orchestration and observability software that helps companies run AI workloads much more efficiently.
Company Launches
Chamber – Autopilot for AI Infrastructure 🚀
See original launch post

TLDR;

Chamber is building AI infrastructure platform that automates governance and resource optimization for enterprise.

Ask: If you’re at (or know) a company spending millions on reserved GPU infrastructure we’d love to talk.

Our Launch Video: https://youtu.be/w5Nk1wleigc

Who are we? We're former Amazonians that built and scaled large-scale infrastructure optimization, delivering hundreds of millions in cost savings, and we’re now bringing those learnings to help other enterprises uncover idle AI infra, accelerate workloads and reduce wasted money on reserved idle GPUs. (Featured in Business Insider)

LinkedIn: Charles, Shaocheng, Jason, and Andreas

Problem: Despite massive AI infrastructure investments, 30–60% of enterprise reserved GPU capacity sits idle in siloed allocations, slowing down teams who need it most, and silently driving up costs. This inefficiency represents $240B+ in annual waste across the industry, and it’s only growing as AI research and development accelerates.

Solution: Chamber puts your AI infrastructure on autopilot. Our agentic AI enabled platform orchestrates, governs, and optimizes your AI infrastructure so teams can run ~50% more workloads on the same GPUs without manual intervention. It operates like an autonomous infrastructure team: continuously monitoring GPU clusters, forecasting demand, detecting unhealthy nodes, and reallocating resources in real time to where they create the most impact. Your ML teams move faster, infra waste drops, and GPU bottlenecks disappear.

  • Discover & optimize idle GPU capacity
    Automatically identifies underutilized GPUs and hidden optimization opportunities across clusters, teams, and workloads.
  • Agentic AI–driven orchestration
    Automatically right-size workloads, manage resource allocations, and schedule jobs across teams based on real-time demand and priority.
  • Self-healing infrastructure
    State-of-the-art bad-node detection with automated remediation to keep clusters healthy and jobs running.
  • Deep AI-powered analytics
    Detect anomalies, forecast usage, and slice and dice workloads by team, user, job type, or priority.
  • Proactive alerts & executive visibility
    Native integrations with Slack, Email, and PagerDuty, and more to deliver real-time alerts, executive digests, and clear action items.

Our Product Demo: https://youtu.be/E8BLg7zi9mc

Who is this for:

  • AI/ML teams looking to move fast and run more workloads without manual GPU allocations, priority spreadsheets, or burning budget on unused GPUs
  • Engineering leaders & executives who need real-time visibility, accountability, and control over GPU spend to deliver higher ROI to their executives and shareholders

A gift from us: We’re offering a complimentary GPU Intelligence Dashboard and advanced monitoring & discovery agent that gives you immediate, production-grade visibility into your AI infrastructure.

  • Automatically discover and expose unused GPU capacity in real time
  • Understand utilization patterns across teams and workloads
  • Receive executive-ready email reports on GPU usage and trends
  • AI driven insights from your cluster utilization metrics

Create an account to start assessing your opportunity to run more workloads in minutes for free.

Want to talk with us? Schedule a call with us here.

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Chamber
Founded:2026
Batch:Winter 2026
Team Size:4
Status:
Active
Location:San Francisco
Primary Partner:Brad Flora