MAATIMAATI

01 / The trace

Everything leaves a trace.

  • A factory leaves emissions.
  • A product leaves a material footprint.
  • A supply chain leaves movements.
  • Energy leaves consumption patterns.
  • Waste leaves evidence.
  • Decisions leave consequences.
The question is not whether traces exist.
The question is whether we can understand them.

A single number, a complex story

4,827,391 kg CO2e

A result is only as strong as the trail behind it.

Illustrative figure for explanation only — not a customer result or a MAATI claim.

Where?
Facility A
When?
Q2 2026
From what?
—
Activity data?
—
Factor?
—
Version?
—
Source?
—
Evidence?
—
Boundary?
—
Assumption?
—

The forensic chain

  1. Source

    Where it originated

  2. Trace

    What it left behind

  3. Context

    The bigger picture

  4. Method

    How it’s quantified

  5. Calculation

    How it’s derived

  6. Interpretation

    What it means

  7. Decision

    What happens next

We don’t start with the answer.
We start with the evidence.

02 / The reconstruction

From disconnected data to a clearer picture

The story behind the number.

Sustainability information exists in fragments — across systems, documents, people and processes. MAATI connects them, reconstructing the story behind every result.

Different data.
One reality.
A connected story.

  • Invoices

    Energy bills, fuel records

  • Meter data

    Electricity, fuel, water, steam

  • Supplier data

    Materials, embodied impact

  • Production data

    Output, batches, process logs

  • Waste records

    Generation, treatment, disposal

  • Logistics

    Transport, movement

  • Laboratory results

    Emissions, water, chemical analysis

  • Regulations

    Applicable requirements

  • External datasets

    Emission factors, LCA databases

We reconstruct the chain

From trace
to understanding.

Every result is connected to its source, context, methodology and evidence — so you can see how it was derived, what it means and how confident you can be in it.

4,827,391kg CO₂e

  1. Result

    The number you see

  2. Calculation

    How it was derived

  3. Activity

    What happened

  4. Source data

    The raw input

  5. Evidence

    Documents, records, measurements

  6. Facility

    Where it occurred

  7. Process

    The bigger picture

  8. Physical reality

    The real-world event

Data has different levels of certainty

A responsible system shows the difference.

Uncertainty is information — not a problem to hide.

  1. Missing

    Information not available

  2. Assumed

    A user-defined assumption

  3. Estimated

    Based on assumptions or proxies

  4. Calculated

    Derived from other recorded values

  5. Verified

    Checked against its evidence

  6. Measured

    Read directly from an instrument or record

Ranked from least to most certain, following the platform’s own data-provenance order and simplified here. Separately, each activity record carries a data-quality tier — Low, Medium, High or Verified — which answers a different question: not how a value was collected, but how far it can be trusted.

A number is a point. Its story is a pathway.

03 / The intelligence

From evidence to intelligence

One reality.
Many questions.

MAATI unifies environmental, social and climate information through a single intelligence foundation — giving every result its context, method, evidence and meaning.

  • How much did we emit?

    Measure with clarity.

  • Where did it come from?

    Trace to the source.

  • What can we change?

    Model for better decisions.

  • Can we trust the result?

    See the evidence.

Multiple perspectives · one connected reality

The intelligence fabric

  1. Data

    From every source

  2. Evidence

    Documents, records, measurements

  3. Methodology

    Standards & logic

  4. Calculation

    Transparent and reproducible

  5. Validation

    Checks and quality

  6. Provenance

    Full traceability

  7. Knowledge

    Context and insights

  8. AI

    Explain, don’t just answer

More than software.
A system for evidence-based decisions.

This describes what MAATI is built toward. What each platform can do today is set out on its own platform page, not here.

Platform guides

See the workflow, not just the claim.

Each guide below is a real, step-by-step walkthrough of the actual product — screenshots from a live MAATI workspace, with the field you should look at on each screen marked, and the parameters that screen actually captures listed underneath.

  • GHG accounting workflow

    Set up your organizational structure, then record and calculate Scope 1, 2 and 3 emissions through to a locked, report-ready inventory.

    Download PDF

  • ESG & double materiality workflow

    Set your organization profile, determine what actually applies to you, run a materiality assessment, and collect real environmental and social data.

    Download PDF

  • Carbon removal & MRV workflow

    Create a project against a real, cited methodology, declare its carbon pools, record a production batch, and calculate the result from the methodology’s own equations.

    Download PDF
Morning sun breaking through low cloud over a green mountain valley

04 / The responsibility

Our commitment

Responsibility is part of the design.

Sustainability information influences real decisions, real people and the real world. We design MAATI to support responsible use, honest interpretation and meaningful action.

  • Transparency

    Show what we know and what we don’t.

  • Integrity

    Methodology before convenience.

  • Accountability

    Be clear about what we establish.

  • People

    Technology should support, not replace, human judgment.

  • Environment

    Respect natural systems and their limits.

  • Long-term thinking

    Value lasting impact over short-term optics.

  • Collaboration

    Work with scientists, practitioners and communities.

  • Continuous learning

    Standards, science and technology evolve — so do we.

The limits we state plainly

  • MAATI does not certify your figures.

    It prepares evidence for independent assurance — it does not replace the people who provide it.

  • MAATI does not make the decision.

    It shows the evidence, method and confidence behind a number. Judging what to do about it stays with people.

  • MAATI cannot improve data it was never given.

    Where evidence is missing, assumed or estimated, it says so instead of filling the gap quietly.

A lone hiker standing on a rock ridge above forested valleys in warm evening light

Know today. Act for tomorrow.

From understanding to a better tomorrow.

Sustainability intelligence is not just about knowing the impact. It is about taking responsibility — for people, nature and future generations.

More informed decisions.
A more resilient world.
  • Cleaner ecosystems
  • Stronger communities
  • More informed businesses
  • A more resilient tomorrow

05 / The name

माटी

MAATI

māṭī · soil, earth

Why we are named for the ground.

माटी (māṭī) is a word for soil and earth in many Indian languages and dialects. Soil is where everything begins, and where everything returns. It holds the trace of what has happened above it.

Sustainability intelligence has to be built the same way — from the ground up, on what is actually there, not on what would be convenient to report. The name is a reminder of that, and the five letters are how we try to honour it.

MMeasure
Start on the ground, not on the slide.
Capture activity data across every scope, by hand or by bulk import.
AAnalyse
Reason from the evidence, in the open.
Resolve emission factors and run the calculation behind every figure.
AAssure
Earn trust before asking for it.
Enforce validation and an approval workflow before anything is locked.
TTrace
Everything leaves a trace — keep it.
Keep every result linked to its source evidence and method, permanently.
IInnovate
Grow as the science grows.
Extend into new methodologies and data sources as the science moves.

Leadership

The people behind MAATI.

  • Mahesh Masura

    Founder & Strategy Lead

    Leads MAATI’s strategy and direction as it builds sustainability intelligence on evidence, not assumption.

    VisionA world where every organisation can measure its impact on the planet with the same confidence it measures its finances.

    Vision & strategy

  • Rahil Ranpura

    Co-founder & Technology Lead

    Leads the engineering behind MAATI — from the calculation engine to the evidence trail behind every figure.

    VisionSustainability numbers that anyone can trace, audit and trust — built into the platform, not bolted on afterwards.

    Technology & engineering

  • Priya Pathak

    Co-founder & Operations Lead

    Leads day-to-day operations at MAATI, turning the platform into a reliable experience for every customer team.

    VisionSustainability work that runs as smoothly as any other part of the business, so teams spend their time acting on the data, not chasing it.

    Operations & delivery
A young seedling emerging from dark soil

Built from
the ground up

The world leaves evidence.
We build the intelligence to understand it.

MAATI

Measure · Analyse · Assure · Trace · Innovate

People · Planet · Progress · Together