Definition & Overview

The Tech Stack for Sustainability Data

Q: How does GLYNT.AI extract data from raw input files?

GLYNT.AI uses a proprietary Few Shot machine learning system that trains a dedicated model for each customer from as few as three sample files, delivering 98%+ accuracy from the start and 99.5% accuracy after human review.

Q: How is GLYNT.AI's Few Shot ML different from large language models (LLMs)?

Few Shot ML trains on just a few sample files per customer, while LLMs train on massive, general-purpose datasets. That makes Few Shot ML faster to deploy, less expensive to run, and far more energy-efficient than general AI tools.

Q: How much energy does GLYNT.AI's AI use compared to other AI tools?

GLYNT.AI’s Few Shot ML uses less than 5% of the energy and water that LLMs consume, and produces less than 20% of the emissions of standard cloud AI tools , training each customer’s model in minutes.

What is a tech stack for sustainability data?

The sustainability data tech stack is the fully integrated set of tools and systems that turns raw input files into audit-ready sustainability data — complete with testing and reporting built in. It’s how GLYNT.AI builds ESG and sustainability data governance into every step, for energy, water, waste and emissions data.

It’s more than a collection of tools: it’s a complete, compliant, enterprise-grade data management and governance system.

GLYNT.AI uses “sustainability data tech stack” and “standard sustainability data layer” interchangeably. “Data layer” emphasizes where this technology and workflow sit within your broader enterprise systems.

WHAT IS IT

The sustainability data tech stack from GLYNT.AI

The sustainability data tech stack is a complete, integrated solution built to meet demanding audit and compliance requirements.

Diagram of the GLYNT.AI sustainability data layer. Raw input files from internal and external sources flow up through eight stacked layers: connectors, site uploads and portals; data extraction (Few Shot ML); data aggregation and harmonization; data-level and system-level testing; business data integration; data management and change management reporting; audit-ready files and documentation; and data and output file customization. Enterprise-grade security and compliance surrounds all layers. The output feeds ESG software, regulatory disclosures and other reports.

WHY IT MATTERS

The sustainability data tech stack is a complete solution for automated data preparation.

GLYNT.AI integrates every tool needed for sustainability data preparation, applies the same system-level tests used in financial reporting, and undergoes an annual SOC audit — so you don’t have to build any of it yourself.

Save time

GLYNT.AI’s integrated tech stack automatically prepares your sustainability data.

Reduce risk

GLYNT.AI’s tech stack delivers audit-ready data from a compliant system.

Data you can trust

GLYNT.AI runs finance-grade, data-level and system-level tests; every number is verified.

Cost effective

GLYNT.AI delivers your first data in days and pays for itself in 4 months.

Scales globally

GLYNT.AI handles multiple languages and character sets, and large global footprints.

FEATURE DETAIL

Tour the features of the sustainability data tech stack

We built the tech stack from customer experience, delivering a purpose-built data solution for sustainability teams.

Connectors, site logins & portals

GLYNT.AI connects to your data however it lives — through APIs and SFTP from enterprise systems, direct connections to utility sites, and upload portals for site-level submissions.

Data aggregation & harmonization

Raw input files vary widely in content and layout. GLYNT.AI uses a standardized data schema to aggregate and harmonize extracted data across your entire global footprint.

Business data integration

GLYNT.AI adds customer business data and metadata — such as site codes, SAP codes, or master vendor IDs — making sustainability data more useful for business decisions, strategic planning, and AI-driven analysis.

Data extraction

GLYNT.AI uses a proprietary “Few Shot” machine learning system for data extraction, adding dedicated models for each customer. This delivers 99.5% accuracy while fully segmenting every customer’s AI models and data.

Data-level & system-level testing

GLYNT.AI runs 65+ data-level accuracy tests, plus system-level tests for completeness, uniqueness, and reconciliation against key ledgers.

Data management & change management reporting

Sites, vendors, data sources, and formats constantly change in sustainability, and each change needs clear reporting. GLYNT.AI’s reports give sustainability, IT, and finance teams the visibility they need to manage and verify data flows.

Data & output file customization

GLYNT.AI customizes data fields and output files for seamless data flows into existing software and tools. Built-in customization is cost effective, as all data and output files go through GLYNT.AI’s rigorous testing and validation process; no customer developers required.

Enterprise-grade security & compliance

GLYNT.AI is audited annually and is SOC 1 and SOC 2 Type II compliant. SOC 1 is the standard public companies use for SOX.

Audit-ready files & documentation

GLYNT.AI provides a complete set of audit-ready assets that help customers streamline audits and reduce audit expense. These include data files, documentation, reporting and SOC reports.

Compare

How does GLYNT.AI’s sustainability data tech stack differ from ESG and carbon accounting software?

GLYNT.AI’s tech stack feeds the ESG and carbon accounting software you already use with finance-grade, audit-ready sustainability data.

A finance-grade data preparation

GLYNT.AI’s tech stack goes beyond a simple data pipeline, delivering sustainability data prepared with the same rigor as financial data.

Purpose-built AI

GLYNT.AI’s “Few-Shot” ML handles the wide variation and constant change in sustainability’s raw input files — speeding up data delivery and reducing manual, error-prone exceptions.

No developers required

As a complete data preparation system, GLYNT.AI integrates and tests every component for you.

THE FAQ

Questions about the sustainability data tech stack

What is GLYNT.AI's sustainability data tech stack?

GLYNT.AI’s sustainability data tech stack is a complete, compliant data management system that captures, prepares, and delivers audit-ready sustainability data into your existing software — replacing the manual data entry and low-code tools most ESG platforms still require.

What is ESG and sustainability data governance?

ESG data governance is the set of controls, tests and documentation that keep ESG data accurate, traceable and audit-ready. It’s different from the “G” in ESG, which means corporate governance. For the environmental data in ESG (energy, water, waste and emissions), GLYNT.AI builds governance into the tech stack: data-level and system-level tests, change-management reporting, chain-of-custody documentation and an annual SOC audit, so your team doesn’t have to build it.

How is GLYNT.AI's tech stack different from ESG or carbon accounting software?

Most ESG and carbon accounting software is built for using sustainability data, not preparing it, so companies still rely on manual entry or low-code tools to get data ready for reporting. GLYNT.AI automates that entire preparation process, delivering clean, structured, audit-ready data directly into the software you already use.

How does GLYNT.AI extract data from raw input files?

GLYNT.AI uses a proprietary “Few-Shot” machine learning system that trains a dedicated model for each customer from as few as three sample files, delivering 98%+ accuracy from the start and 99.5% accuracy after human review.

How is GLYNT.AI's Few-Shot ML different from large language models (LLMs)?

Few-Shot ML trains on just a few sample files per customer, while LLMs train on massive, general-purpose datasets. That makes Few-Shot ML faster to deploy, less expensive to run, and far more energy-efficient than general AI tools.

How much energy does GLYNT.AI's AI use compared to other AI tools?

GLYNT.AI’s Few-Shot ML uses less than 5% of the energy and water that LLMs consume, and produces less than 20% of the emissions of standard cloud AI tools, training each customer’s model in minutes.

How does GLYNT.AI test and validate sustainability data?

GLYNT.AI runs data-level tests that check individual figures for accuracy, plus system-level tests for completeness, uniqueness, and reconciliation against key ledgers. Every source file also passes through a library of automated test scripts, along with any custom tests a customer requires.

Can GLYNT.AI customize data fields and output formats?

Yes. GLYNT.AI can add fields like site codes, GL codes, and SAP identifiers, and deliver data in the format your existing systems already use — procurement, FP&A, facilities management, or BI tools. Every customization goes through the same testing and validation process, so no development work is required on your end.

How does GLYNT.AI handle changes to sites, vendors, or data formats?

GLYNT.AI tracks every change with receipt logs, exception reports, and full chain-of-custody documentation, so your team always has a clear audit trail of what changed and when.

Is GLYNT.AI SOC 1 and SOC 2 compliant?

Yes. GLYNT.AI is audited annually and is SOC 1 and SOC 2 Type II compliant.

Is GLYNT.AI more cost-effective than building an in-house data system?

Yes. Because GLYNT.AI’s platform costs are shared across many customers, it typically costs significantly less than building and maintaining an equivalent system in-house, without requiring your own developers to build or maintain it.