Product Overview

A quick look at the GLYNT.AI solution

Audit-Ready Sustainability Data

Prepared for ISSA 5000 and other audit standards

Sustainability Data Layer

Works with the software and AI you already use

Approval Workflows for Sustainability Data

Four-Eyes review for audit compliance

Finance-Grade Sustainability Data

The same rigor as financial data

Integrate with Financial Data

Reconcile against your financial ledger

AI-Ready Sustainability Data

See what’s missing or flagged before deadlines

Powered by Green AI

Built for low energy use and emissions

Best Practices for Sustainability Data Management

Manage data instead of wrangling it

Enterprise Security

Privacy, security, and controls

Sustainability Data Accuracy

We test your data so you don’t have to

Comprehensive File Capture

Extract data from scans, portals, and messy formats

Customized Reporting

See what’s missing or flagged before deadlines

Audits & Assurance

Traceable data, approval workflows with SOC compliance

Business Value Add

Customize output files for CSRD, IFSR, CBAM, UKSRS

Energy Data Management

Granular data for transparency and cost reductions

Waste Data Management

Pull files from everywhere, send data to anywhere

Scope 3 & PCFs

Stop chasing suppliers, move to finance-grade quality

Blog

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Customer Stories

Industry applications for GLYNT solutions

Guides

GLYNT’s expertise and thought leadership

5 Ways Machine Learning Will Disrupt How Energy Products Are Sold

by | Feb 2, 2018

Getting utility bill data is hard. Basic frustrations persist, including inconsistent online access and plenty of paper bills — nearly half of those sent! WattzOn has built an advanced machine learning (ML) software system to make utility bill data faster, better and cheaper.

As with other industries and applications, ML is hyper-efficient at certain tasks. This creates a new set of industry economics, and the cost of utility data is now a fraction of that previously. The result of the technology advance is a dramatic change in industry economics. New opportunities open up and data flows more freely.

This post makes some fairly audacious claims. But they are easy to validate. Just do a simple online search for “AI will change everything”. Hundreds of well-reasoned articles will pop up that make the same economic arguments set out here.

Here at WattzOn we’re excited about our machine learning system, SNAP, and how it brings this forecast of change to life. As many analysts have noted, the economics of machine learning are hugely disruptive. The key conclusion is that at a strategic level ML leads to harsh industry economics, including winner-take-all situations. But, the upside from an ML system is significant. We agree with a recent McKinsey report that concludes: 

“[ML delivers] a triple prize: satisfied customers, lower costs, higher growth.”