Raw compute
for structured
intelligence.

Why HypaVOLT

Built for humans and agents tackling workloads others avoid.

  • 01

    Sharded GPU Compute Grid

    Our shard process breaks workloads into basic units of electrical consumption and spreads them across a global network of GPUs.

  • 02

    Radically Lower Costs

    Inference starts at $0.20/GPU-hour. Because low-end GPUs contribute meaningfully to the grid, we tap a supply pool hyperscalers can't price against.

  • 03

    Batch & On-Demand Inference

    Built for real production workloads: batch vectorization, indexing, and on-demand AI inference.

  • 04

    Developer-Ready

    Simple APIs and flexible integrations to plug into your existing stack.

Pricing

Stop overpaying for GPU compute.

Tap into our inference farm at a fraction of traditional cloud costs. Process and index 100M+ objects without the cloud markup.

Starting at$0.20/ hour

Volume discounts available for enterprise pipelines.

The shift

Not another GPU cloud. Sharded grid wins here.

Centralized clouds scale by renting top-end GPUs at a premium, with everything else sitting idle.

HypaVOLT shards workloads at the electrical-consumption layer so low-end GPUs become meaningful contributors. That changes both the supply pool and the economics.

The old way
  • Centralized hyperscaler pricing
  • Top-end GPUs only, rest idle
  • Supply capped by data-center buildout
  • Cloud markup on every workload
The new way
  • Sharded compute across the full GPU spectrum
  • Low-end hardware becomes real capacity
  • Supply scales with node-operator incentives
  • On-demand and batch, starting at $0.20/GPU-hour
Use cases

Compute for the next era of intelligence.

  • 01

    Search & Query Layers for RPC Providers

    Vectorize on-chain and RPC data for natural-language querying and semantic routing.

  • 02

    Vectorization at Scale

    Generate embeddings across millions of documents, objects, or events in parallel.

  • 03

    Custom Intelligence Pipelines

    Bespoke ingestion, transformation, and retrieval pipelines for enterprises and institutions.

  • 04

    Longitudinal Research

    Continuous processing of long-horizon datasets: clinical, financial, or scientific.

  • 05

    Knowledge Graph Construction

    Extract entities, relationships, and structure from unstructured enterprise content.

  • 06

    Real-Time Forecasting & Scenario Analysis

    Run high-frequency inference on market, operational, or risk signals as they arrive.

  • 07

    Merchant POS Intelligence

    Transform point-of-sale streams into retrievable insight for operators and analysts.

  • 08

    Digital Twin, Sensor & Drone Data

    Process telemetry and geospatial streams into queryable models of physical systems.

  • 09

    Open Intelligence & Public-Good Monitoring

    Power open research on civic, environmental, and humanitarian datasets.

Customer story

Our need was elastic. And now so is our bill.

Brenden Tacon · Head of Product & Growth · Presearch.com

We're building Presearch's proprietary search index. Processing hundreds of millions of pages with a small embeddings model meant spiking to several hundred GPUs, then dropping back. But AWS and Digital Ocean only sold us overpowered, rationed hardware priced for capacity we didn't need.

HypaVOLT lets us scale to whatever the job needs and pay only for the work. We're past 50M indexed pages and on track to hit 400M+ in under six months. Fast enough that we had to rearchitect our vector database to keep up.

Integrations

Plug into your existing stack.

  • OpenSearch / Elasticsearch
  • Data lakes & warehouses
  • Custom APIs
  • Node / RPC infrastructure
  • MCP Server
Get started

We make it easy to get started based on your needs.

Enterprise

Hands-on onboarding with custom ingestion, large-scale vectorization, and tailored implementation support.

Self-Serve

An API-first experience to connect data, vectorize, and ship. The architecture is designed to become increasingly agent-native over time.

Build faster.Process more.Spend less.