Impact

Show your work.

Reduce first with MAIZX. Measure what you reduced with the Carbon Ledger. Compensate only the residual. Every figure carries an evidence label.

Results

What we have achieved.

Observed in production: workload-level Scope 2 attribution, measurable CO2 reductions through carbon-aware placement and scheduling, and audit-ready evidence behind every figure. Each card is labeled by evidence type so observed, validated, and modeled outcomes stay visually distinct.

Observed
50-63%
CO2 reduction

Observed in production workloads. Varies by workload and region. Not a guarantee for any specific workload.

R&D validated
Up to ~85%
CO2 reduction

Demonstrated in controlled MAIZX optimization environments. Not yet generalized to all production workloads.

Modeled
4K-10K tCO2/yr
5 MW deployment range

Reduction within the observed operating range; up to ~14K tCO2/yr modeled upside. Modeled, not achieved.

Thesis

Static placement is the bug. Adaptive orchestration is the fix.

Most cloud architectures pick a region once and never revisit the choice. Grid intensity, energy price, and demand change every minute. Climate value comes from acting on those signals, not from reporting on them after the fact.

Status quo
~520 gCO2/kWh avg

Static placement

workload runs here all day - fixed region00:0006:0012:0018:0024:00

Region chosen at deploy time. Emissions track whatever the local grid happens to do.

GREENPOW
~210 gCO2/kWh avg

Adaptive orchestration

runrunrun00:0006:0012:0018:0024:00

Placement responds to grid intensity, cost, latency, and constraints in real time, with every decision recorded against workload-level Scope 2.

MAIZX in motion

Every reduction starts as a routing decision.

MAIZX decides where and when each workload runs, weighing carbon alongside cost, latency, sovereignty, and availability. If a workload can shift without breaking its constraints, it does.

Signals weighed in real time

Carbon intensity

Live gCO2/kWh per region and hour, ranked against current grid mix.

Energy cost

Spot and contracted prices, including curtailed-renewable opportunities.

Latency

Per-route latency budgets so placement never sacrifices SLA targets.

Sovereignty

Jurisdiction and data residency treated as hard constraints, not preferences.

Urgency

Deadline, elasticity, and shiftability define how aggressively temporal shifting applies.

Availability

Capacity, utilization, and failure signals across regions and nodes.

Carbon Ledger

Infrastructure telemetry, not an ESG report.

Filter, compare, drill down, export. The Carbon Ledger is the operational anchor of GREENPOW: workload-level Scope 2 attribution with evidence labels on every value.

Carbon Ledger - live view

Scope 2 attribution per workload, tenant, region, and time window. Backed by live telemetry when connected, otherwise by a clearly-labeled sample dataset.

Sample dataset
Compare with
None
0 kg CO2e
Total Scope 2
0 kWh
Energy used
0 gCO2/kWh
Avg. grid intensity
0
Telemetry entries

Scope 2 over time

Primary: All workloads, tenants, regions

No telemetry in the selected window.

By region

  • -

By workload

  • -

By tenant

  • -

Evidence mix (share of Scope 2)

Observed 0%Measured 0%Modeled 0%R&D validated 0%

Figures carry evidence labels (Observed / Measured / Modeled / R&D validated) per our claims policy. Sample mode uses representative values for illustration only.

Methodology and evidence

Every figure answers five questions.

Methodology and evidence labels live together. The accordion below covers commitments. The scale beside it explains what each label means and where it applies.

Evidence labels

Achieved evidence
Modeled estimates
Forward-looking
  1. Observed01

    Seen in production workloads on real infrastructure. Varies by workload and region.

  2. Measured02

    Quantified from instrumented telemetry with a defined measurement methodology.

  3. Modeled03

    Calculated from a documented model and inputs (for example, deployment size, grid intensity, utilization).

  4. R&D validated04

    Demonstrated in controlled MAIZX optimization environments, not yet generalized to all production workloads.

  5. Projected05

    Forward-looking estimate based on stated assumptions. Not a commitment.

  6. Target06

    An internal goal we are working toward, not an achieved result.

Projections, modeled upside, benchmarks, and targets are never presented as achieved facts.

What you can verify from this view

  • Scope 2 per workload

    Per workload, tenant, and service. Never aggregated into a single account-wide number.

  • Time-window attribution

    Hourly, daily, and rolling windows aligned with how CSRD asks for Scope 2.

  • Side-by-side comparison

    Workloads, tenants, and regions compared with absolute and percentage deltas.

  • Placement decisions

    The MAIZX log: which workload moved where, when, and which signals drove it.

We do not claim zero emissions, fully sustainable infrastructure, or guaranteed carbon reduction. We use precise language: reduce, optimize, improve visibility, support lower-carbon decisions, enable carbon-aware scheduling, and compensate residual emissions.

Next

See the platform behind the proof.

Bring your workloads, regions, and constraints. We will show MAIZX placement decisions and Carbon Ledger evidence on a setup that looks like yours.