Trainy
Provide infrastructure for managing GPU clusters for training and serving, enabling AI teams to efficiently schedule, allocate, and reliably use GPU resources.
At a Glance
- AI Research Teams
- Machine Learning Engineers
- HPC Data Centers
- GenAI Startups
AI Tools by Trainy
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Trainy
GPU Infrastructure for AI Teams
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Products & Services
GPU cluster management software with job scheduling, priority assignment, and resource control.
Open-source experiment tracker with dual-logging and history export capabilities.
Multi-cloud GPU orchestration service for deploying and scaling AI workloads across any cloud provider.
Performance profiling dashboards to identify bottlenecks and boost training speed.
Market Position
Trainy differentiates itself by offering a cloud-agnostic, single-config solution that automates complex GPU networking and cluster management, lowering the barrier to scaling AI models.
Leadership
Founders
Roanak Baviskar
Co-founder & CEO. Previously Audio team lead at Hive AI. Holds a degree in CS & Mathematics from UC Santa Cruz.
Andrew Aikawa
Co-founder & CTO. Previously Lead Machine Learning Engineer at Hive AI. Holds a Physics Ph.D. from UC Berkeley.
Executive Team
Roanak Baviskar
Co-founder & CEO
Expert in GPU infrastructure; former lead at Hive AI.
Andrew Aikawa
Co-founder & CTO
Physics Ph.D. with deep expertise in ML engineering and cluster optimization.
Founding Story
Founded by former Hive AI engineers Roanak Baviskar and Andrew Aikawa. The company was started to solve the operational hurdles ML engineers face when managing GPU clusters. They pivoted to include 'Pluto' after recognizing the need for an open-source experiment tracker.
Business Model
Revenue Model
SaaS subscription for experiment tracking (Pluto) and usage-based/on-demand fees for GPU orchestration.
Pricing Tiers
Free for existing Trainy customers; 3 months free early-bird promotion.
Charges only during active training runs; no cost for idle GPUs.
Target Markets
- AI Research Teams
- Machine Learning Engineers
- HPC Data Centers
- GenAI Startups
- Multi-node scaling for large model training
- Reducing GPU idle time and training costs
- Transitioning from Neptune to open-source experiment tracking
- Cloud-bursting for on-premise clusters
- Whitefiber, Inc.
- Early adopters of Pluto experiment tracker