DODIL provides a unified platform that aggregates SOC‑II‑compliant GPU and CPU capacity from a global network of data centers, delivering high‑performance compute for AI workloads at 60‑70 % lower cost than traditional cloud providers. The service offers managed provisioning, monitoring, auto‑scaling, and raw compute spaces through a web portal and API, simplifying resource allocation and compliance for developers and engineering teams.
Funding
Funding not disclosed
Founders
Product
Problem
AI developers and enterprises face high cloud compute costs and operational complexity when provisioning large-scale GPU or CPU resources, limiting experimentation and scaling of machine‑learning workloads.
Solution
DODIL aggregates capacity from a global network of SOC‑II compliant distributed data centers and offers it through a unified platform that delivers 60‑70 % lower compute pricing. The service abstracts the underlying infrastructure, providing managed provisioning, monitoring, and scaling so users can focus on model development rather than hardware logistics. Compute resources are available as both fully managed services and raw compute spaces, enabling flexible integration with existing pipelines. Access is controlled via a web portal and API that handle authentication, billing, and compliance reporting, simplifying the procurement process for AI workloads.
Target Audience
The primary customers are AI enthusiasts, application builders, and engineering teams at startups or enterprises that require cost‑effective, high‑performance compute for machine‑learning model training and inference.
Features
- Global pool of SOC‑II compliant data center nodes delivering high‑performance CPU/GPU instances at reduced rates
- Managed compute service with automated provisioning, health monitoring, and auto‑scaling for AI workloads
- Raw compute spaces (bare‑metal or virtualized) for custom environment configuration and direct hardware access
- Unified API and web dashboard for resource allocation, usage analytics, and cost tracking
- Pay‑as‑you‑go pricing model that reflects the 60‑70 % cost advantage over traditional cloud providers
- Built‑in security and compliance controls, including SOC‑II audit readiness and encrypted data transit
- Community waitlist portal for early adopters and ecosystem building among AI practitioners