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Mark Edwards talks with Martha Amram of Glynt.ai.

Revisiting their previous conversation,Mark and Martha have an in-depth conversation, spanning exciting innovations in AI and Machine Learning, no-code platforms, the increasing demand for carbon emissions data and how companies can now make money from their data.

Background

With a PhD from MIT, Martha's background is in economics & finance. From there, she moved into the energy sector and for the last 8 years, she has been running Glynt, which captures energy data and turns it into a useful product.

Right now, there\\u2019s a pressing need to record emissions in order that they can be reduced.\\xa0

Glynt.ai

Glynt is the market-leading producer using AI of carbon emissions. They are at the forefront of not only change (reducing emissions) but also of making profit from that change. So, AI and data are absolutely critical.

There\\u2019s now a big market in carbon credits - selling them directly, selling them as options and futures and embedding them into green loans - Sort of the Fintech of carbon emissions.

Two Major Pivots for Glynt

Realising that building templates didn't scale, they built a ML (Machine Learning) system to eliminate the need for templates, but also to avoid using expensive ML specialists. They created a system that could be operated by no-code users.

Doing this, significantly reduced costs to the business and was an important strategic pivot for Glynt.

Glynt's second pivot was coming out of Covid - in late Spring 2021 - Everybody was exhausted after 20 very difficult months and nobody had time to think - It could be called an "Enterprise Attention Deficit Economy", where people just wanted easy solutions to their problems.\\xa0

So, to address this attention deficit economy, Glynt simply configured their existing AI solution to focus on carbon emissions.

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The Future for Glynt

There\\u2019s now an underlying, new demand for carbon emissions data and the ability to make money from it.

Glynt's extensible solution can produce Scope 2 & 3 emissions data. Having combined those two things and being an emissions data producer, they are simultaneously connecting everything to the financial market.

Supplying data is Part A of contributing to climate change solutions, Part B is showing people how to profit from their own data - And this is where Glynt is poised to make a huge difference in accelerating the cycle of change.

Currently, every CEO has an issue with reporting emissions data. Clearly this is a risk management challenge for them, and this is fuelling a huge demand for for carbon emissions data and for Glynt's services.

Regardless of the size of the enterprise, the pressure is now on to have really accurate data today and to be able to report reductions tomorrow. Climate tech is now a huge market - with $40 billion a year spent on solar, wind and building in efficiencies.

That complete market needs data to drive down next year\\u2019s data, next year\\u2019s reported emissions.

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Biggest Business Lessons Learnt

Martha's\\xa0 approach is:

1. "Get ready to be lucky" - What can I do now to be prepared to take that random call that\\u2019s gonna be the game-changer..? Where are my gaps?
2. Take the big mission and break it down - Deliver your message so your team can take it forward, build a very tightly run organisation, particularly as everybody is working from home - Clear communication from the top and setting the culture is a \\u2018must have\\u2019.

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Links:

https://www.linkedin.com/in/martha-schary-amram-b9164328/
https://glynt.ai/