Phaidra
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About
Phaidra provides an AI control platform tailored for the orchestration of power, cooling, and workload management systems within high-density data centers, often referred to as AI factories. The primary objective of the system is to maximize energy efficiency, specifically targeting the "tokens per watt" metric. By integrating various components of the facility's tech stack—from the Building Management System (BMS) to the individual racks—Phaidra ensures that the entire infrastructure operates as a single, coordinated unit of compute. The technology centers on the use of agentic AI that autonomously manages critical hardware like liquid cooling Distribution Units (CDUs) and chiller plants. These self-learning agents are designed to maintain thermal stability and have been shown to reduce thermal spikes associated with AI workload ramps by approximately 80%. Additionally, the platform features a conversational LLM agent that acts as a specialized assistant for facility operators. This allows staff to query operational data and troubleshoot issues using natural language, significantly accelerating root-cause analysis. This tool is intended for data center operators and facility managers overseeing large-scale, mission-critical environments. It is specifically optimized for facilities deploying advanced hardware, such as NVIDIA gigawatt-scale AI factory designs. Because it allows for higher cooling temperature setpoints without compromising GPU safety, it is highly valuable for organizations looking to reclaim power from their facility infrastructure to support higher IT capacities and revenue-generating compute. What sets Phaidra apart is the background of its creators and its focus on closed-loop, autonomous control rather than simple monitoring. Founded by former Google and DeepMind engineers who were responsible for pioneering data center energy efficiency projects, the platform applies reinforcement learning to industrial systems. Unlike traditional rule-based controllers, Phaidra’s agents are self-learning, allowing them to adapt to changing environmental conditions and complex system interdependencies that manual management might overlook.
Pros & Cons
Reduces thermal spikes by approximately 80% during AI workload ramps.
Proven track record from founders who reduced Google's cooling bills by 30%.
Converts complex data center troubleshooting tasks from days to minutes using natural language.
Operates autonomously 24/7 to maintain stability without constant manual intervention.
Increases available IT power by safely raising facility temperature setpoints.
Requires deep integration with Building Management Systems (BMS).
Limited relevance for smaller data centers without high-density AI hardware.
Pricing is not publicly disclosed and requires a custom demonstration request.
Specific software compatibility for non-NVIDIA ecosystems is not fully detailed.
Use Cases
Data center operators can automate cooling adjustments to maximize energy efficiency and reduce Power Usage Effectiveness (PUE) metrics.
Facility managers can use the conversational AI to identify and diagnose hidden infrastructure issues in minutes using natural language queries.
Infrastructure architects can design AI factories with higher cooling temperature thresholds to redirect more power to revenue-generating GPUs.
Mission-critical engineering teams can utilize 24/7 autonomous monitoring to prevent hardware damage from rapid thermal spikes during compute bursts.
Platform
Features
• workload orchestration
• closed-loop reinforcement learning
• precision thermal setpoint control
• pue optimization
• thermal spike reduction
• conversational llm for troubleshooting
• liquid cooling cdu management
• autonomous cooling control
FAQs
How does Phaidra improve thermal stability in data centers?
The platform's AI agents reduce thermal spikes by nearly 80% when workloads ramp up. This autonomous control ensures that cooling systems react instantly to changes, protecting hardware and maintaining uptime.
What is the benefit of the conversational LLM agent?
The LLM agent allows facility operators to troubleshoot and analyze facility data using natural language. It can reduce the time required for complex operational analyses from days or weeks to just a few minutes.
Does Phaidra help increase IT capacity?
Yes, by optimizing cooling efficiency and enabling higher temperature setpoints safely, it reduces the power required for facility support. This freed-up power can be redirected to increase the number of revenue-generating GPUs.
Can Phaidra manage liquid cooling systems?
Phaidra is designed to optimize the entire cooling stack, specifically including liquid cooling Distribution Units (CDUs). This ensures that liquid cooling infrastructure operates efficiently alongside the broader chiller plant.
Who developed the technology behind Phaidra?
The technology was developed by a team including the engineers who built DeepMind's AlphaGo and those who led Google’s data center cooling optimization projects, resulting in significant energy savings.
Pricing Plans
Enterprise
Unknown Price• Autonomous liquid cooling control
• CDU and chiller plant optimization
• Conversational troubleshooting agent
• 24/7 mission-critical monitoring
• Workload management integration
• Thermal stability reporting
• Custom deployment support
• Security and compliance audits
Job Opportunities
Head of Marketing
Maximize AI factory efficiency and token generation with AI agents that orchestrate cooling, power, and workload management to reduce energy spikes by 80%.
Benefits:
Competitive compensation & meaningful equity
Medical, dental, and vision insurance
Unlimited paid time off (minimum of 20 days per year)
Paid parental leave
Flexible stipends for workspace, well-being, and professional development
Experience Requirements:
10+ years of marketing experience in tech
Leadership experience at a Series B or later-stage company
Proven track record of driving measurable pipeline and revenue impact
Experience building and executing marketing strategy from zero (zero-to-one)
Strong background in positioning, messaging, and storytelling for complex technical products
Other Requirements:
Located in the USA or Canada (Ontario, British Columbia, or Alberta)
Legal authorization to work in the specified locations without sponsorship
Ability to operate in highly technical environments (AI, software, infrastructure)
Alignment with core values: transparency, collaboration, operational excellence, ownership, and empathy
Active camera connection required for Google Meet interviews
Responsibilities:
Define and own Phaidra’s global marketing vision, strategy, positioning, and narrative
Build the marketing function from the ground up, including processes, tools, and budgeting
Build and execute demand generation programs that drive qualified pipeline and revenue
Lead content and brand initiatives across blogs, videos, podcasts, and social media
Track, report on, and optimize marketing performance using data-driven KPIs
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