Energy · Compute · Infrastructure

AI compute is bottlenecked by power.

Seditio builds GPU compute infrastructure on curtailed renewable energy.

The opportunity

01 / Constraint

New transmission and generation take five to seven years to build. AI demand has outrun the grid's ability to deliver.

02 / Opportunity

Utility-scale solar generates more electricity than the grid can absorb. Gigawatt-hours of zero-carbon energy with no path to demand.

03 / Approach

Co-locate GPU infrastructure with stranded renewable generation. Built for batch training, inference, and rendering workloads.

What we build

Compute

Dense NVIDIA Blackwell-class clusters optimized for training, batch inference, and rendering workloads.

Power

Direct interconnection with utility-scale renewable assets. Energy supply contracted for the long term.

Storage

Battery energy storage sized to shift daytime generation into 24-hour compute load. No grid dependency.

Sites

Each site located where renewable supply exceeds local grid demand. Compute moves to where the power is.

Who it's for

Sustained training capacity for foundation models, fine-tuning runs, and large-scale RL workflows. Reservable in 10–100 MW blocks.

Batch inference, document processing, and embedding generation at scale. Latency-tolerant pipelines that benefit from low-cost compute.

Animation, VFX, scientific simulation, and synthetic data generation. Deadline-driven workloads with predictable scheduling.

Hyperscalers and neoclouds seeking geographically diversified capacity. Sovereign-AI buyers seeking clean-power compute.

Contact

Investor & partnership inquiries.

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