Commodity price predictions using A.I. predicts the future prices of commodities, so that you make better decisions. uses artificial intelligence to analyze and make sense of a wealth of standard and alternative data sets.



The problem:

If you have commodities or raw materials in your cost base, you need to forecast future prices. Investment banks employ teams of analysts to do this. Most other businesses don’t. They don’t because they can’t afford to. In practice, it’s often one element of someone’s role, such as a buyer or a treasurer.

And it’s a hard task thanks to:

  • Volumes of data: Due to increasing transparency in the markets, the number of data sets available is getting ever larger. And the number of alternative data sets available is mushrooming
  • Separating the wheat from the chaff: KnoKnowing which data is important, continuous analysis, and making the right inferences is a growing challenge.
  • Human flaws: People often get ingrained ideas about how a market ‘should’ work, and emotion can cloud judgement.
  • Volatility: Prices are increasingly volatile - most commodities and raw materials prices swing by 30-60% a year.

The solution: was created because continuously monitoring the ever-growing number of news sources, analyzing the dizzying number of data sets, and deciding which events impact the future price, is an impossible challenge for any person or team.

What does is to harness the power of artificial intelligence on standard and alternative data sets to forecast commodity prices.

Key elements

  • Multiple time horizons: predicts what the prices will be in 1 day, 1 week, 1 month, 3 months, 6 months and 1 year time horizons
  • Global: covers the European, North American and Chinese futures markets
  • Conviction: The predictions include lower and upper bound numbers that are ‘80th percentile confidence bounds’ - so we would expect the actual values to be inside these limits 80% of the time
  • Performance reporting: includes an indication of how successful each prediction has been
  • Daily:’s predictions are updated on a daily basis

Which commodities does cover?

We are always adding more commodities to

Any not covered today can be added relatively quickly on-demand – get in touch to discuss your needs.


Wheat, Corn , Sugar , Cotton, Ethylene


Power, Gas , Diesel


Aluminum, Copper, Zinc, Lead, Cobalt, Nickel, Steel rebar

The Benefits



Enables better
decision making

Enables better
decision making

  • A vast number of data sets are analyzed every day, including alternative data
  • The confidence level of each prediction is stated, so you know when conviction is strong
  • A machine learning loop means’s capability continuously improves as each day passes





  • Easy to scale across many commodities
  • Takes seconds to implement
  • Significantly more cost effective than employing multiple analysts across all commodities



Goes beyond
human capability

Goes beyond
human capability

  • No human is able to scrutinize the vast number of data sets that does every day
  • Emotion, bias and other human flaws do not cloud the predictions
  • Calculations are run every day, without fail


How we started it is part of Flow&Ebb. Flow&Ebb are specialists in commodity price risk management. We help organizations to protect their margins from volatile commodity prices. We do this through both consulting and innovative technology.

Most of our clients buy commodities either directly or within their direct materials or raw material purchases.

Our clients include
  • Industrial product manufacturers
  • Food & beverage manufacturers
  • FMCG manufaturers
  • Retailers & wholesalers
  • As well as any large consumer or producer of energy

Our Advisory Board

Andrew Burgess

Andrew Burgess

Andrew has worked as an advisor to C-level executives in Technology and Sourcing for the past 20 years.

Andrew Burgess is a thought-leader and practitioner in Artificial Intelligence and Robotic Process Automation, and is regularly invited to speak at conferences on the subject.

He is a strategic advisor to a number of ambitious companies in the field of disruptive technologies. He has written two books; ‘The Executive Guide to Artificial Intelligence (Palgrave MacMillan, 2018) and, with the London School of Economics, ‘The Rise of Legal Services Outsourcing’ (Bloomsbury, 2014). He was recently awarded ‘Automation Champion of the Year’ by the Global Sourcing Association. He is a prolific writer on the ‘future of work’ both in his popular weekly newsletter and in industry magazines and blogs.

Andrew Burgess

Chris Gayner

Chris is a Director at Symphony Labs.

Chris Gayner has spent the last 15 years working in fast paced, growth orientated environments – spanning Technology, Media, Consulting and Professional Services - driving business outcomes through innovative and creative solutions.

Chris's role as Director of Symphony Labs aims to develop and align a network of clients, partners and leading minds across the Intelligent Automation eco-system, to solve some of the biggest challenges business leaders face around the future of work. Chris is also a contributor to The All-Party Parliamentary Group on Artificial Intelligence (APPG AI) and commentator on RPA, Intelligent Automation and AI Technology. He is a big believer in the power of technology plus people to overcome critical business and societal challenges.


If you would like a demo, more information or to discuss working together, please get in touch.