As an investor one of the best parts of the job is backing an all-star team solving a really complex problem-one which believes in shaping the wave rather than riding on it.

TrueGradient is a self-serve AI supply chain planning platform. The word ‘chain’ in supply chain doesn’t give the true picture of how complex modern supply chains are. Modern supply chains are highly complex networks-interconnected, dynamic systems with multiple nodes, dependencies, and flows.

The founders of Truegradient have worked on supply chain optimization systems across firms like Amazon, Walmart, Fidelity investments, Dunzo and Mondelēz handling $200+ Billion sales every day.

They observed that while these giant firms can afford a huge team of data scientists it is not possible for every consumer goods, retail or e-commerce company. But it’s a big pain point in the life of every consumer company, thousands of them. And it’s a very difficult problem to solve with ripple effects on every aspect of the business. A problem that costs businesses millions in lost revenue and inefficiency.

After having worked with customers whose yearly revenue ranged between $25 Million to $400 Million Truegradient team found out the cost of inefficiencies businesses are paying without any way to plug these leaky buckets.

They found that a company with, let’s say, $50 million in revenue, might be holding about $1 million in excess inventory. And at the same time they could be missing out on almost $2 million in potential sales. And a company with $400 million in revenue. They could be sitting on almost $5 million in excess inventory. And losing out on a whopping $20 million in potential sales.

This clearly highlights the importance of having a system that connects demand and inventory planning.

Currently businesses try to solve it with excel based solutions which are basically linear models which quickly fail to deliver in the complex interconnected world of the modern supply chain.

Truegradient’s solution is a self-serve AI model which can be used both by business teams and data science teams. It offers nonlinear optimization models, which can take into account many of the external factors.

It uses the concept of AutoML and causal neural models, which automates the complex tasks involved in building and deploying machine learning models.

A business just needs to share the factors which impact it, which varies from business to business, which Truegradient’s platform ingests and trains the model to predict accordingly. The platform will figure out what are the right models that need to be used for this particular prediction. And if you want to dive deeper you can run experiments, fine tune models, customize them to fit your specific needs.

And it doesn’t limit itself to historical data. It factors in real time information. Changes in demand weather patterns. Even social media trends. It’s constantly adjusting.

But inventory planning is just one piece of the puzzle. Truegradient offers businesses a whole suite of functionalities to optimize every stage of their supply chain. From demand forecasting to inventory optimization, to even price, and promotion planning.

Using its strategic pricing optimization functionality businesses analyze things like competitor pricing, seasonal trends and get recommendations for the best prices to maximize revenue and profit margins.

It helps businesses with markdown optimization. Which is about managing excess stock efficiently. It recommends when and how much to discount items so businesses clear out extra inventory without sacrificing too much profit.

So no more guessing games. No more overstocking things that won’t sell or being understocked during a demand surge. Or discounting things more than needed.

TrueGradient represents the kind of technology democratization we love to back at Neon. It is reshaping supply chain optimization for mid-sized companies by providing them with advanced and easy-to-use AI-driven tools.

We’re excited to back Truegradient’s mission to help thousands of businesses across the world to reduce waste, improve demand and inventory forecasting, and ultimately drive revenue growth.