Vishal Chatrath, on how AI companies are rising to the challenges posed by the Covid19 pandemic

Alexandra Mousavizadeh
5 min readMay 14, 2020

Vishal Chatrath is the co-founder and CEO of, a Cambridge based company known for its unique AI platform that helps people make better business decisions and delivers significant value across the enterprise.

In this interview he explains how AI might help us better understand ‘black swan’ events and be better prepared to meet the challenges they create. Vishal also argues that governments need to assimilate more potential protocols and many different versions of the future, rather than one ideologically defined strategy; He suggests too that a lack of competence in system building has caused serious problems for the UK during the Covid19 pandemic.

This article is part of Tortoise Media’s pre-read content for the upcoming Global AI Summit on Friday 15 May. It’s open to all — register your place here.

How are, and other artificial intelligence companies, experiencing the pandemic?

New artificial intelligence technologies are emerging that can work with very small amounts of data to simulate scenarios. This is opening the way for having a mechanism which can be used to respond to ‘black swan’ events; before they even happen. The way this works is through technology — popularly called a digital twin. It is possible to generate synthetic data, rapidly, and essentially create scenarios that simulate crises, analyse them, and identify if an organisation has the resilience to cope. This is important today, as many of the executives in CEO positions around the world have no experience of how to deal with crises of this magnitude; it’s a very unique and unprecedented sort of situation.

At we saw change and disruption very early on. In some of the largest supply chain companies in the world; whilst there was very little data to plan against, it was clear something was happening. It was possible, though, to put solutions in place that allowed for planning; answering questions about how much capacity some companies needed to hedge, how long until they could start to recover, and so and so forth. We’ve seen a lot of companies accelerate the development plans with these digital twin technologies, precisely because of how applicable they are in the current circumstances.

Technically, what might the role of AI be in tackling elements of this disruption?

We are, in this case, talking about decision engines that can enable supply chain optimisation, and help companies to handle this kind of turbulence. We are likely to see this kind of tool embedded as part of the core processes of more and more companies who rely on multimode processes for their operations. We have learnt two big lessons, the first is that these systems have to be able to perform with a small amount of up-front data. And the second is that they need to be able to absorb human expertise. This is to say that experienced people can superimpose their expertise on the decision modelling. We used to focus on sentiment analysis, but there is a huge amount of noise in those processes, what we are looking at now is a system that doesn’t replace the human, but rather gives the human a joystick with which to impinge, literally, on the model and see how it responds, and then to iterate and repeat the process. This is where the big aspects of planning for a future post-COVID-19 really begin.

On a global scale, we are seeing serious economic fragilities, what systems have failed here?

The over optimisation of global supply chains for economies of scale stands to make them very fragile. A perfect example is immediately after the Fukushima earthquake, when something like 90% of the world’s capacity for pigment for painting cars black was from a single plant in the area. So it happened that the cost of often getting very cheap black cars, was sometimes not getting them at all.

It is very difficult to forecast ‘black swan’ events but countries that have more protocols, and more rigorous planning for them are coping better. We are already seeing these countries fare better in terms of their responses and the fallout. As we go forward the number of black swan events worldwide is likely to increase, not least because of severe weather events. So over the next 20 years say, we are faced with some significant stresses to our existing systems. COVID-19 is a wake-up call; to think seriously about our resilience. We might move into a phase where citizens demand evidence of strategic inventories of PPE, other medical supplies, food etc. These types of plans, as well as demonstrable strategic reserves, will be demanded by citizens and investors.

There’s discussion of a return to the local, what are your thoughts on this taking place in Europe?

Much of northern Europe is not demographically or culturally equipped to re-industrialise. There does seem to be a shortage of young people willing to do particular forms of work, and so automation is going to play a big role. There’s going to be a lot of talk about near-shoring and whether it’s viable for countries in northern Europe. This calls back into the question the ability to plan for large, multidimensional decision-making processes. In these cases, a platform like ours really thrives, because we essentially focus on intelligence as knowing what to do next; making informed decisions from a perspective. Artificial intelligence is also about making decisions and so these machine learning tools that allow for planning against scenarios which do not require millions or billions of data points are a very promising interface.

Where do we go from here?

COVID-19 is a serious wake up call. Governments, like many of the businesses that we work with, need to start integrating processes for planning. These processes need to be able to cope with unforeseen circumstances and events, perhaps functioning with synthetic data, alongside expertise in disaster planning. Governments need to assimilate more potential protocols and many different versions of the future, rather than one ideologically defined strategy. The systems currently in use in the UK are way behind, and therefore the knowledge of the pain-points for the supply chain of crucial services — which are being so badly undermined right now — weren’t known. Neither were the KPIs for successful action during this crisis. Much of this boils down to the lack of much competence in system building within government. A background in policy-making is no longer enough. All ministries and governments need a CTO — individuals who have built systems that can incorporate cutting-edge technologies, and cope with ‘black swan’ events.

This article is part of Tortoise Media’s pre-read content for the upcoming Global AI Summit on Friday 15 May. It’s open to all — register your place here.



Alexandra Mousavizadeh

Hi I am Alexandra, a partner at Tortoise Media where I work in the Intelligence group