ghg.services

AI-assisted carbon accounting · In development

Emissions data
you can trace.

We’re building a platform that connects source data, AI-assisted collection and transparent calculations. Join us as a pilot partner to test it on real operational data and shape what we build.

Become a pilot partner Explore the workflow

Seeking pilot partners worldwide. First markets: the UAE, Saudi Arabia, the EU and the US.

3
Scopes
15
Scope 3 categories
Pre-pilot
Stage
Interview log Simulation · sample data

Simulated target workflow. Fictional data, illustrative calculations. No live integrations.

Target workflow: employees answer through chat, call, email or voice message; analysts inspect the data and calculations here.

At the end of each tab the terminal offers an Excel export: click it and press y, or download the sample workbook (.xlsx) directly. Fictional data.

Our mission

Make carbon accounting something companies can own.

We’re building a platform powered by AI and modern data technologies to help companies collect and analyse data, calculate emissions and prepare traceable reports. It is designed to reduce manual work and give companies control over the process, with expert support when needed.

Fig 01 your process, powered by the platform

How it works

Turn conversations into structured emissions data.

Much of Scope 3 data lives in people’s heads and in scattered files. We start by asking the right people the right questions, then make every step of the path to a number inspectable.

In development · Not yet validated on real data · Looking for a pilot partner to test it with

Fig 02 four kinds of source, one ledger under them all

  1. Step 01

    Interview

    An AI interviewer asks employees and data owners structured questions in plain language, by call, email, chat, voice message or any channel people already use, and follows up when an answer is incomplete.

    AI
    asks, follows up, flags gaps
    Aims to cut
    chasing people for answers
    Fig 03 one question, two outcomes

  2. Step 02

    Structure

    Answers from one person or a thousand, in any channel, become the same structured fields. A missing value stays open. Nothing is guessed.

    AI
    turns any answer into the same fields
    Aims to cut
    manual re-keying
    Fig 04 a thousand people, any channel, one set of fields

  3. Step 03

    Data Intelligence

    Bring together spreadsheets, corporate data stores, transport logs, logistics records and operational documents. AI-assisted extraction, search and analysis are designed to find emissions-related activity, connect records, flag inconsistencies and surface missing data.

    AI
    extracts, matches, flags suspicious records
    Aims to cut
    combing through files by hand
    Fig 05 find emissions signals across your data

  4. Step 04

    Report

    Turn reviewed data into traceable reports. AI drafts reporting tables and explanations and highlights gaps. You review each result alongside its activity, factor, assumption and evidence before exporting.

    AI
    drafts tables and explanations, highlights gaps
    Aims to cut
    assembling the report by hand
    Fig 06 one number, traced back

Principles

Built to be checked.

Traceable

Every number carries its evidence.

Each result is broken down into activity, unit, factor, assumption and evidence. If something is an assumption, it says so.

Separated

AI extracts and analyses. Rules calculate. People review.

Models help collect, extract and analyse data and suggest connections and explanations. The calculation itself is deterministic and reproducible. People resolve ambiguities and sign off.

Honest

Clear about our stage.

We are pre-pilot: in development and not yet validated on real data. Demonstrations use sample data and say so. We do not claim certifications, results or customers we do not have.

Fig 07 who does what

Scope 3 data collection is structured around the 15 categories defined in the currently published GHG Protocol Corporate Value Chain (Scope 3) Standard. The GHG Protocol is revising its standards, and ghg.services is independent of it and not endorsed by it.

Pilot partnership

Let’s build around your real-world challenges.

We’re seeking a pilot partner to work with us on real operational data. Together, we’ll develop and test the platform’s services for an agreed carbon-accounting and reporting use case.

We are currently in discussions with prospective pilot partners.

Seeking pilot partners worldwide. First markets: the UAE, Saudi Arabia, the EU and the US.

Become a pilot partner

welcome@ghg.services

Proposed pilot format · details agreed per partner
Who it suits
Organisations with energy, fuel, travel, procurement or logistics data and a named data owner. Large operational sites such as airports are our first focus.
What you get
A data map, a first inventory for the agreed categories, a calculation ledger with evidence, and a reduction workshop.
Built together
Priority Scope 3 categories, import templates and the review workflow, shaped around your real data.
What we ask
Access to data, one or two process owners, regular working sessions and honest feedback.
Terms
Scope, timing and commercial terms are agreed with each partner. A case study is published only with your written approval.
Data handling
NDA before any data is shared. Where data is processed and which AI providers are involved is agreed in writing before any interviews or document processing take place.

Company

The team behind ghg.services

Maksim Irishkin

CEO, co-founder

Technology and innovation manager with a background in rare, rare-earth and precious metals extraction, and earlier experience running innovation projects and working with startups in mining and metals. He leads ghg.services’ strategy and partnerships, bringing industrial experience to the way emissions data is collected and reviewed in resource-intensive operations.

Vladimir Ageykin

CTO, co-founder

Software architect with 15+ years of experience delivering 30+ production applications across GenAI, financial systems and enterprise platforms. He has led engineering teams building LLM-based products and data-heavy platforms on Python and cloud infrastructure. At ghg.services he leads the technology: AI-assisted data collection and analysis with a transparent, deterministic calculation engine.

LinkedIn ↗

Shape it with us.

Pre-pilot. Test it on your real data and shape what we build.

Become a pilot partner See the pilot format
$ welcome@ghg.services

Email us your sector and the data you hold