Cloud GreenOps Solutions

Cost and Carbon Efficiency in Enterprise AI and Cloud

Greenpixie is the trusted source of GreenOps data for AI-first organisations. Bring technology and sustainability together to unlock responsible growth in cloud and AI.

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Consistent multi-cloud methodology

Track emissions across AWS, Azure and GCP, like for like.

AWS61%

Azure25%

GCP14%

3,518 mtCO₂e combined

Total carbon

3,518mtCO₂e

Total electricity

15.19MkWh

Total water

2.56ML

Carbon per dollar

11.2gCO₂e/$

Identify Top emitting cloud regions

us-east-1us-west-2eu-west-1ap-southeast-2

Find your Top emitting business units

Platform

52.8

Data & Analytics

41.2

AI Research

28.5

Carbon as a currency

Take action with sustainability data that's granular enough for your FinOps practice. Put carbon alongside cost in allocation, recommendations, budgeting, forecasting and gamification.

#Business unit · LeaderTrendmtCO₂e

Compliance & AuditR. Holm · Head of Compliance

↓ 8%9.7

Mobile AppsN. Acharya · VP Mobile

↑ 7%12.4

Identity & AccessL. Becker · Director, Security

→ 1%14.6

Internal ToolsT. Reilly · Engineering Ops

↓ 12%19.8

AI ResearchP. Patel · Head of AI

↓ 92%13.5

Full visibility over AI usage

Understand, compare, and optimise AI usage across your cloud estate, reducing cost, carbon, energy and water as you scale.

AI carbon

13.1mtCO₂e

AI water

167,692L

AI electricity

31,857kWh

AI spend

$272,756

Impact by token type

Input (uncached)

Input (cached)

Output

Impact by model

GPT-4.1

1,157

864

GPT-4o

230

GPT-4o Mini

GPT-4.1 Nano

GreenOps Training & Certification

Get certified in the sustainable cloud operating model with our GreenOps Academy - and understand the business case for sustainability in cloud and AI.

Definition of GreenOps
The GreenOps Flywheel
Finding the right data
GreenOps Advocacy

4.82out of 5(695 reviews)

"This course is outstanding! I love how it explains complex concepts in simple terms, making it accessible for everyone.
Highly recommended!"

Tetiana FedrikoPrincipal FinOps Architect, NatWest

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Decision-making tools

Run "what-if" scenarios on your cloud and AI decisions - and model their impact at the planning stage.

Current

m6a.8xlarge

us-east-1 · io2

Carbon7,260 kg

Cost$4,116

→

Proposed

c7g.xlarge

eu-north-1 · gp3

Carbon2,714 kg

Cost$1,799

Right-sized saving / year$2,3174,546 kg CO₂e

Available via API

Automate your cloud and AI emissions data, and plug it directly into your FinOps and BI workflows.

Call our API

→

Flow into your BI tool

→

Visualise for your team

Sample API response

{
  "sku": "JFMHJK32Z5JP9WMH",
  "instance_type": "m7gd.xlarge",
  "region": "eu-west-1",
  "pricing_unit": "Hours",
  "kwh_per_pricing_unit": 0.00898093,
  "total_tonnes_co2e_per_pricing_unit": 0.00000383069,
  "total_water_litres_per_pricing_unit": 0.01498652,
  "line_item_usage_type": "EU-BoxUsage:m7gd.xlarge"
  // refreshed hourly, ISO 14064-3 verified
}

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Improve Scope 3 reporting on cloud emissions

Greenpixie covers all cloud services across AWS, Azure and GCP.

But the granularity goes a lot deeper than service-level. Emissions can be reported at account-level, product-level, business unit-level, geographic location, account owner and by any other configuration your tagging supports.

Refreshed hourly, location-based, Scope 3 inclusive, and ISO 14064-3 verified, GPX Data can be delivered via API or processed by Greenpixie and delivered as an enriched Cloud Billing Report.

This raw data approach ensures compatibility with your data lake and seamless integration into Power BI, QuickSight, Tableau or whichever FinOps tool you already use.

Book a call about this use case

Pietro BertazziChief Policy and Projects Officer, CDP

Data intelligence you can trust

Methodology for auditable reporting and informed action

When emissions data informs business decisions, it needs to stand up to scrutiny. Unlike approaches that estimate emissions using spend-based proxies, Greenpixie models emissions from actual cloud usage data across AWS, Microsoft Azure, and Google Cloud. With coverage spanning every cloud service, you get a complete and defensible view of your cloud and AI footprint.

The result is emissions intelligence you can trust to:

Understand where emissions are coming from
Identify the highest-impact opportunities for reduction
Make infrastructure decisions using accurate, location-specific carbon data
Report with confidence using transparent, auditable methodology

Our methodology is academically reviewed and independently verified in accordance with ISO 14064-3, prepared with reference to ISO 14064-1, and designed to be in line with the GHG Protocol Corporate Standard.