Data & infrastructure is Metahive's compute layer for organizations sizing AI workloads, so that they know where their work runs, who operates it and what energy it draws.
Combine compute, power, cooling, network and operating responsibilities into a candidate envelope.
Physical and operator prerequisites.
Combine compute, power, cooling, network and operating responsibilities into a candidate envelope.
Location, tenancy and physical prerequisites.
Planned design remains distinct from commissioned capacity.
Planned design capacity remains separate from commissioned service capacity.
Compare required resources and sensitivity with an eligible service boundary.
Candidate service capacity and custody boundary.
Declared resource needs and sensitivity.
Compare required resources and sensitivity with an eligible service boundary.
Workload, custody, site and capacity requirements.
Eligible site or explicit mismatch.
Custody, resource and site requirements must all fit the proposed placement.
Bind maximum admitted cost before work under one identity.
Eligible identified placement.
Applicable tenant/site/period maximum and policy.
Same-identity settlement or retained uncertainty.
Bind maximum admitted cost before work under one identity.
Tenant/site/period and money/token maximum.
Policy identity and unresolved reservation state.
The reservation binds a maximum cost to the original tenant, site and period.
Compare scheduler/service evidence and settle the original reservation.
Original reservation for later settlement.
Independent identified work record.
Actual consumption/result or explicit unknown usage.
Compare scheduler/service evidence and settle the original reservation.
Tenant, product, unit, time and observed use.
Actual cost, justified unused balance or uncertainty.
Uncertain use does not automatically release the unused reservation.
Attribute site-hour metering using matching IT use without hiding idle energy.
Independent site/hour metered energy including overhead.
Observed tenant/site/hour IT use.
Attribute site-hour metering using matching IT use without hiding idle energy.
Meter and tenant IT-use records for the same site/hour.
Facility overhead, allocated energy and explicit unattributed remainder.
Attribution requires matching site and hour records; idle or unattributed energy stays visible.
Physical and operator prerequisites.
Combine compute, power, cooling, network and operating responsibilities into a candidate envelope.
Location, tenancy and physical prerequisites.
Planned design remains distinct from commissioned capacity.
Planned design capacity remains separate from commissioned service capacity.
Candidate service capacity and custody boundary.
Declared resource needs and sensitivity.
Compare required resources and sensitivity with an eligible service boundary.
Workload, custody, site and capacity requirements.
Eligible site or explicit mismatch.
Custody, resource and site requirements must all fit the proposed placement.
Eligible identified placement.
Applicable tenant/site/period maximum and policy.
Same-identity settlement or retained uncertainty.
Bind maximum admitted cost before work under one identity.
Tenant/site/period and money/token maximum.
Policy identity and unresolved reservation state.
The reservation binds a maximum cost to the original tenant, site and period.
Original reservation for later settlement.
Independent identified work record.
Actual consumption/result or explicit unknown usage.
Compare scheduler/service evidence and settle the original reservation.
Tenant, product, unit, time and observed use.
Actual cost, justified unused balance or uncertainty.
Uncertain use does not automatically release the unused reservation.
Independent site/hour metered energy including overhead.
Observed tenant/site/hour IT use.
Attribute site-hour metering using matching IT use without hiding idle energy.
Meter and tenant IT-use records for the same site/hour.
Facility overhead, allocated energy and explicit unattributed remainder.
Attribution requires matching site and hour records; idle or unattributed energy stays visible.
An illustrative process for comparing site constraints and reconciling identified resource use.
Additional mechanisms are described in the technical reference.
What the research says
EU data centers already draw a large share of electricity and the EU aims to triple capacity, while each hardware generation does more per watt. Placement stays the buyer's decision, so Metahive Builder tests a site against the workload before purchase and Metahive books each workload's energy apart from overhead.
Compute procurement, a new site and a private deployment begin with different constraints.
Define workload, service units, location and operational responsibilities.
Compare fit, power, cooling, network and physical capacity.
Connect custody, model access and operating control to a deployment design.
A larger equipment list can still fail the intended service.
Follow equipment through the rack, room, building and plot.
Check inference memory, placement, concurrency and compute limits.
Compare energy and capacity scenarios with declared assumptions, then plan the measurements required at deployment.
A chief sustainability officer decides when to move a growing AI workload; the plan shows the limit and how sure the estimate is. Illustrative.
Systems behind it
Research, compute & Tier 1
Metahive places the workload on its managed bridge, and later on its own sites, and books its energy apart from site overhead.
3D micro data center design & simulation
Metahive Builder shows whether space, power, cooling or memory runs out first at a planned site, before hardware is bought.
Private computation & model orchestration
Synapse keeps sensitive workloads behind a model boundary, so each provider receives only what a task needs.
Yes. A bounded engagement can deliver a source-linked configuration, workload scenarios, critical constraints and the evidence needed for an investment or build decision.
Compute buyer. Define workload, service units, location and operational responsibilities.
Site planner. Compare fit, power, cooling, network and physical capacity.
Institution. Connect custody, model access and operating control to a deployment design.
Model the physical system. Follow equipment through the rack, room, building and plot.
Model the workload. Check inference memory, placement, concurrency and compute limits.
Examine operation. Compare energy and capacity scenarios with declared assumptions, then plan the measurements required at deployment.
Model the physical system. Follow equipment through the rack, room, building and plot.
Model the workload. Check inference memory, placement, concurrency and compute limits.
Examine operation. Compare energy and capacity scenarios with declared assumptions, then plan the measurements required at deployment.
A proposed compute-site scenario showing the relationship between equipment, energy and inference.
Follow the storyWhere should your next AI workload run, and who should be able to say what energy it draws?
Discuss infrastructure requirements