“AI enables companies to go beyond gaining an operational edge – it creates fundamental new revenue opportunities if applied correctly.”

That’s the conversation that some of the world’s largest CPG’s find themselves having when partnering with Manmit Shrimali, cofounder of two-year-old AI startup, Turing.

As AI has become an enterprise buzzword and started to drive meaningful change across a number of industries – divisions such as product development, manufacturing, and supply chain have yet to be fully transformed by AI advances, but just might be the most lucrative.

Every year, the world’s largest CPG companies like Coca Cola KO and P&G develop and launch hundreds and thousands of new products – from detergent to shampoo. Before it can hit shelves in a store or even reach your mailbox, these products must first undergo a complex development cycle called the “new product innovation (NPI)” phase.

McKinsey has consistently rated consumer goods amongst the least digitally leveraged industries. Lack of digital tools and infrastructure needed to modernize development processes has left CPG companies struggling to grow their market share and has left them vulnerable to competition. While close to 90% of Fortune 500 R&D leads have reported that they want to implement AI into their 5-year digital strategy, very few have been able to do so while realizing any functional, operational insight or improvement.

The NPI process alone – product ideation, development, and prototyping – can take between 9-12 months for major companies.

Functionally – for a company producing a novel product in the food & beverage or skincare space – this means thousands of customer interviews, formulations being turned into prototypes, and re-assessing customer enthusiasm.


For most companies, the NPI process is a major innovation bottleneck and exposes them to being disrupted by other incumbents and competitors.

This is where Turing comes in. By leveraging novel advances in AI, Turing helps the largest of enterprises break their innovation bottlenecks.

Manmit Shrimali and Ajith Govind, the founders of Turing labs, explain below how and why they set out to solve one big problem of CPGs – how to develop winning products in weeks not months or years.

“Less is more when it comes to leveraging data,” said Ajith Govind, Co-founder and Chief Product Officer of Turing. “These companies don’t have time to aggregate the volumes of data that are scattered across their enterprise on forgotten hard-drives and spreadsheets. We built Turing to require 50% less data than traditional algorithms to empower companies to achieve record-breaking discoveries with minimal effort.”

“The AI is just one part,” added Manmit Shrimali, Co-founder and CEO of Turing. “We knew to create real change, our approach would have to address the entire workflow. Product developers need to collaborate seamlessly across all stages of product development. Our digital workflow enables CPG companies to go from concept to commercialization within a single system, with AI guidance and oversight at every step.”

Turing’s cloud-based platform works by ingesting enterprise marketing, R&D, and consumer, chemical composition, and costing data from a number of different sources in different formats. CPG companies are leveraging the platform to assess their ideas virtually while benefiting from AI recommendations. 

The result? Products are getting made faster and with markedly higher customer delight and revenue results.

Turing is disrupting the traditional CPG development process through it’s modeling and simulation (M&S) platform that uses modern AI techniques to improve a company’s product development speed by 10x.

According to Alan Maingot, (CEO of Maingot & Kaw Innovation, and retired CPG industry innovation executive who spent 36 years at P&G), historical approaches to building (M&S) platforms have struggled to gain industry widespread adoption and success. This was driven by these platforms requiring the industries’ data be digitized and reformatted. Additionally, user interface complexity required data management expertise (versus the formulator themselves). This results in a well-intended M&S program expecting to deliver faster, better, and cheaper innovation, ends up costing a lot more than budgeted; takes much longer to achieve the desired outcomes; and never gets used broadly across the organization.

Maingot has observed the Turing AI enabled platform to be different., He’s noticed a few clear distinctions in its advantages for the CPG industry. 

  1. Onboarding becomes simple without the need for historical digitization and data reformatting
  2. it is broadly adopted, even by formulators that are not M&S or data science experts
  3. It uses an intuitive, cloud based workflow that allows teams to collaborate remotely, putting formulation teams virtually back in the lab (important in the pandemic)
  4. It democratizes organization know-how.

We were able to sit down with Alan to understand exactly what the biggest problems in AI implementation are, and why the world’s largest companies are partnering with Turing to bring novel products to market. Answers below.

1) Why are CPGs investing more right now in improving their product or innovation pipelines?

“The CPG industry is highly competitive. It is impacted by both the end consumer that the brand is competing on wallet-share for, as well as the retailer where the brand is competing for shelf space/digital priority. It is usually a low cost of entry industry (relatively), with a high purchase frequency (versus durables). This means you need to be the consumer’s first choice several times a year to win in this marketplace. This drives the need for more and constant innovation in CPG.

2) CPGs must sit on massive amounts of data – why have CPG companies struggled historically with utilizing their data in the innovation and GTM process?

The data in CPG comes from multiple sources including consumer preferences, sensory data, technical data, material data, processing data, stability data, etc. These data inputs are spread across various metrics and formats that have historically been difficult to digitally connect. This is compounded by the fact that the sheer pace of innovation, and data associated with each initiative, results in a massive amount of data that has been difficult to keep track or access.  Turing allows for the capture of this data (without costly time and investment in reformatting) and then enables access to it. In the CPG world, where it is estimated that more than half of the R&D investment is spent learning something that you already know, the Turing platform is a game changer. With smart access to your existing data, the need for new data becomes more targeted. Innovation done on the Turing platform is better, faster and cheaper!

3) Where do you think CPGs can gain competitive advantage?

Historically, competitive advantages were derived from better consumer insights; or better technology; or innovating faster or cheaper. The Turing platform opens a whole new competitive advantage opportunity. The AI augmented platform does a better job at the marrying of technology and the consumer insight. It can help identify more un-obvious technology applications, or better technology solutions, in many cases using existing technology and data.  This creates more innovation opportunities that can be better tuned to win with the consumer.  This will result in better solutions that are identified faster and cheaper.

 4) How should CPGs think about implementing AI to drive product innovation? Where does modeling and simulation specifically come into play?

We always tell companies the best time to think about an AI implementation strategy is to start now. The use of AI will allow innovators to extract more learning from existing data, faster. This could level the playing field with most large CPG brands seeing their source of competitive advantage being diminished.

Previous M&S platforms were difficult, time-consuming and costly to implement, with many limited to finding and explaining a current problem/solution. The addition of AI will make this faster, at lower cost, but more importantly move the M&S to be better at predicting new outcomes. It will truly allow the use of existing data to create a new opportunity, and more specifically direct specifically what new data is required. As this becomes the norm, current approaches to CPG innovation could become obsolete. Implementation of the AI enabled platforms is easier and cheaper.

Tools like Turing are giving CPG companies one of the biggest operational and innovation advantages they’ve ever had. Turing’s SAAS model allows for quick adoption across the enterprise and its modern machine learning techniques enable brands to for the first time, take advantage of the mountains of R&D data they’ve assembled.

Other high-flying startups like Palantir and Flatiron Health have proven that turning unstructured data into structured, query-able insights can enable massive competitive edges in even the most complex industries. Having IPO’d for $26 billion and been acquired for $3.5 billion, respectively, these companies have proven that transforming data into insights can be a highly lucrative venture play.

With the $50 Billion R&D industry at its fingertips and backed by Y-Combinator and other top Silicon Valley investors, Turing faces a similar opportunity, if it can continue to pull its magic off, it has the chance to eat at an already huge, and rapidly growing pie. 

If data is the new oil, Turing is helping organizations mine, refine, analyze, and test the lucrativeness of that oil – without having to run a single trial.