Plutoshift Secures Funding From Akron Fusion Ventures, Strengthening Presence In Northeast Ohio

Investor commits funding to Performance Monitoring Platform For Industrial Processes, Providing Manufacturers With A Unified View To Reduce Resource Consumption And Drive ROI.


PALO ALTO, Calif. — May 18, 2020 — Plutoshift, the leader in data intelligence for industrial processes announced it has secured funding from Akron Fusion Ventures, a venture capital fund in Akron, OH with an investment strategy to connect coastal ecosystems with Northeast Ohio.

Plutoshift has developed a specialized view of process performance for industrial companies, offering a unified window into manufacturing operations through highly sophisticated software that leverages Artificial Intelligence to drive proactive insights. 

By unlocking insights from existing data sources in real-time, Plutoshift enables industrial companies to have a holistic view of key cost drivers and resources that impact their business. This approach allows operators, managers and remote workers to stay better informed and take proactive action. The company works with a variety of industries including Food & Beverage, Manufacturing, Oil & Gas, Chemical, Power & Renewables, and related industrial verticals. 

The new investment and partnership will be used to help Plutoshift expand and strengthen its presence in Northeast Ohio where Akron Fusion Ventures has deep roots and a proven track record for bringing Silicon Valley startups to the region. 

“We are very excited to be partnering with Bill Manby and the entire team at Akron Fusion Ventures. The Northeast Ohio region represents a large opportunity for Plutoshift given the number of manufacturing and consumer goods businesses” said Prateek Joshi, Founder and CEO of Plutoshift.

“We work with companies out of Silicon Valley and bring their innovative solutions to the heartland of America. Northeast Ohio is home to hundreds of successful manufacturing enterprises and a growing startup environment. We are excited to partner with Plutoshift and bring their GROUNDED AITM solution to companies in our area” said Bill Manby, Founding Partner of Akron Fusion Ventures. 

Plutoshift was founded in 2017 by Joshi with the vision of connecting the constantly changing realities of the physical world with the monitoring power of intelligent software. This effort resulted in helping industrial operators and remote workers harness the power of existing plant data related to operations, finances, and maintenance spread across different systems. By providing a fundamentally different way of looking at processes that drive their businesses, Plutoshift aims to provide an unprecedented level of information access to operators and managers.

Joshi is an Artificial Intelligence researcher, an author of 13 books, and a TEDx speaker. He has been featured in Forbes 30 Under 30, CNBC, TechCrunch, Silicon Valley Business Journal, and many more publications. He graduated from the University of Southern California with a Master’s degree specializing in Artificial Intelligence. He has previously worked at NVIDIA and Microsoft Research.


About Plutoshift: 

Prateek Joshi launched Plutoshift in late 2017 with the vision of connecting the constantly changing realities of the physical world with the monitoring power of intelligent software. This effort resulted in helping industrial operators harness the power of existing plant data related to operations, finances, and maintenance spread across different systems. Plutoshift is the leader in data intelligence for industrial processes. 


Their cloud-based solution monitors the performance of industrial processes in an automated way for manufacturing businesses. Plutoshift’s GROUNDED AI™ technology transforms passive legacy monitoring systems to active performance monitoring in industries like water, food, beverage, brewing, chemicals, and energy. This enables operators to automatically monitor critical processes and have access to actionable information in real-time. Plutoshift has offices in Palo Alto and Denver.



Melissa Dunn

Director of Marketing, Plutoshift 


Business Water: The Value of Artificial Intelligence in Achieving Sustainable and Resilient Corporate Water Strategies


Will Sarni, Founder and CEO, Water Foundry and Prateek Joshi, Founder and CEO, Plutoshift


Access to water is one of the greatest challenges to business continuity and growth. A key component of this challenge is the effective operational management of water, which plays a critical role in how much of this resource is utilized. Businesses across a range of sectors such as agriculture, energy, food and beverage, and manufacturing are discovering the value of investing in access to water supplies, water use across their value chain (e.g., supply chain, operations and product use) and improvements in the efficiency and effectiveness of infrastructure and assets to manage water (e.g., treatment systems). Businesses also have a critical role to play in ensuring access to water for their customers, workforce, and communities. Increasingly, consumers, customers, investors, non-governmental organizations (NGOs), and civil society favor “brands with purpose” which includes consideration of how businesses are stewards of water.

Download the White Paper here:

Whitepaper_ Business Water_FINAL

Bridging The Gap Between AI Promise and Results: 3 Actionable Steps

By Prateek Joshi:

Analyst firms like Gartner and Forrester have been advising their clients and the industry at large for several years about the dramatic changes automation and AI will bring to the global economy. According to Gartner’s 2019 CIO survey, the number of enterprises implementing AI grew 270% in the past four years. Companies ranging from the manufacturing sector to finance and energy are feeling the rush to identify and implement AI applications that can help them become more data-savvy and profitable in the modern economy.

But in this modern-day data gold rush, few companies are experiencing as smooth or efficient an implementation process as they would like, and even fewer are seeing the focused results they were hoping for with their AI projects.

Challenge 1: Getting up and running

 In our recent survey report of 250 manufacturing professionals with insight into their companies’ AI projects, we found that 72% said they had taken far more time than anticipated to implement the necessary data collection processes for implementing AI. This lack of mature data-collection infrastructure, as well as other factors, has continued to stall companies’ efforts to fully digitize.

When you take into consideration the challenges of laying the groundwork for an efficient AI implementation, it’s not surprising that only 17% of respondents said they were actually at the full implementation stage of using AI at their company. On the other end of the scale, 20% said their company was still assessing the internal resources needed to implement an AI project. In the middle, about 24% said their company was still getting familiar with AI and assessing the potential business and financial value AI could bring.

Solution: Ditch the one-size-fits-all mindset

Companies should find tailor-made technologies that cater to their specific wants and needs. When partnering with an AI firm that can take all of your company’s unique data-collection and business circumstances into consideration, you can more clearly define and develop an implementation strategy that works for your specific business outcomes and can start to provide returns on the bottom-line sooner.

Challenge 2: Dealing with overwhelming scope

 As the analyst community rightfully points out, AI is capable of taking on many different business tasks: usually, ones that are repetitive, data-intensive or need to be performed around the clock. Because of its utility, many companies are finding it challenging to choose clear goals and business objectives for their AI projects. Only 57% said their company implemented AI projects with a clear goal while almost 20% implemented AI initiatives due to industry or peer pressure to utilize the technology.

Given the immense promise and wide range of applications of AI, respondents naturally had diverse goals for their projects:

  • Overall cost savings (54%)
  • Automating tasks (49%)
  • Achieving a more productive workforce (49%)
  • Improving efficiency in business processes (49%)
  • Improving the quality of their products or customer experience (49%)

Solution: Identify crystal-clear outcomes for your AI projects

A vital step in implementing successful AI projects is identifying specific business outcomes and goals. When companies are on the same page about how they define success with AI, they are better positioned to achieve their objectives.

The right AI partner can help your company select appropriate business goals and define a successful ROI. They can also keep the project transparent by measuring performance in real-time and make adjustments as needed.

Challenge 3: Lacking internal support

As with any period of transition, many companies are facing challenges aligning their internal resources in order to fully support an AI project. 34% said their company has struggled to keep its AI projects in scope because there was a lack of expert guidance at the planning phase of the project.

Additionally, 62% said their company took more time than anticipated to acquire internal buy-in and commitment in implementing AI projects; 60% also said their company struggled to come to a consensus on a focused, practical strategy for implementing AI.

When companies are not aligned behind the goals and the strategy of AI project, the entire process can suffer as a result: 34% said their company experienced an internal lack of engagement with AI projects due to a lack of confidence in the technology.

Solution: Create a data-driven culture

An AI initiative cannot be passed down from the board room without internal buy-in from the rest of the company. The right AI system can empower individual operators to take action on data and improve their overall job performance and experience. With an AI system that is accessible and centralized, no matter who the stakeholder is, they have the chance to see their own opportunities for ROI — whether it is financial or organizational.

Set your company up for success

By taking a thoughtful and intentional approach to implementation, companies of any size can quickly achieve positive business outcomes with AI through three steps: ensure your data collection infrastructure is adequate, define clear business objectives, and reinforce a company-wide commitment to AI.


Why Manufacturing Companies Continue to Struggle with AI Implementation Projects

By Prateek Joshi 

Manufacturing companies know that Artificial Intelligence (AI) can have multiple business advantages for the frontline team and on the overall bottom line. But despite companies’ best intentions and AI’s clear potential, many companies struggle to fully utilize AI. This is leading them to reevaluate their strategy on how to leverage AI for their business, according to our new report

The usage of AI  at the enterprise level is continuing to grow, but the  projects are often loosely defined and can take longer than anticipated to show returns. This has the potential to limit the progress that AI can provide. To further understand the hurdles standing in the way and opportunities AI can bring to manufacturing, we surveyed 250 manufacturing professionals who have visibility into their company’s AI strategy.

Continuing The March Toward AI Implementation

Companies have good intentions when they begin the AI implementation process, but the complexity of AI can pose problems and cause companies to reevaluate their strategy. 

  • 61% said their company has good intentions but needs to reevaluate the way it implements AI projects
  • Only 17% of respondents said their company was in full implementation stage of their AI projects
  • 34% said their company has struggled to keep its AI project(s) in scope because there was a lack of expert guidance at the planning phase of the project


What is Really Holding Companies Back

Having a mature data collection and storage system is essential for AI implementation projects. Without the ability to collect and store  data in a timely manner, manufacturing companies can’t get far with AI implementation. Manufacturers are realizing it takes more time than anticipated to get their data systems up and running. 72% of manufacturing companies said it took more time than anticipated for their company to implement the technical/data collection infrastructure needed to take advantage of the benefits of AI.

Internal buy-in is important for any company project, but it’s especially important for something as complex as AI. Just like marketing, business development, or any other business function, commitment from key stakeholders is essential for success.

Internal buy-in from employees needs to be taken into account when implementing AI projects. 62% said their company took more time than anticipated to acquire internal buy-in and commitment in implementing AI. This lack of internal buy-in has also caused 34% of employees to say that there is a lack of engagement toward these projects.

Important Factors For Successful AI Projects

We found that issues with internal buy-in, decisions regarding who should use the data and lack of budget consensus related to AI projects can slow down implementation in the manufacturing industry.

It’s important to have a mature data collection and analysis infrastructure and to agree on specific business outcomes before implementing and incorporating AI into an industrial workflow. Multiple reasons are given when companies make the decision to begin implementing AI. 54% said that cost savings were the top business problem that they were trying to solve, followed by 49% that said automating tasks was the top reason.

These kinds of projects can lose focus within the company and encounter multiple problems. Less than half (47%) said their company has kept AI projects in scope and focused on deliverables. Moving to a focused approach that can manage the complex process of AI can help to eliminate these issues and help companies stay focused on the long-term goal.

The use of AI technology in the manufacturing industry has the potential and opportunity for companies to empower the frontline team with automated performance monitoring for any industrial workflow. AI can help businesses drive ROI by reducing resource consumption, operating costs, and reliably predict the current state of their business predictions, whenever they need it. 

How do your company’s experiences with AI match up to the respondents? Read more about the report and the methodology here. 


Industrial Automation: 4 Industrial AI Predictions for 2020

By Prateek Joshi:

2019 was a banner year for AI! Almost every business magazine and tech publication published a deluge of articles about AI and its impact on the industrial world and industrial automation. While some of the speculations about AI were overblown, the majority of the attention dedicated to the state of AI by analysts and the media is well warranted.

AI’s impact on industrial automation has already dramatically changed the way companies think about their operations and how they collect and use their data. 2020 will undoubtedly see some of the recent trends in AI continue to intensify, but what else should industrial operators and C-level executives expect for the start of the new decade? Here are four predictions for the world of industrial AI in 2020:

  1. Business Intelligence will Become More Accessible

Access to data is critical for any industrial operator, but many companies are hindered by siloed data sources that cannot be easily accessed by the entire company. Business functions such as budgeting, sales, and performance monitoring all rely on data that’s often needed in real-time.

Data analysts in large organizations are under increased pressure to make actionable recommendations out of unstructured and siloed data. There are now vertical-specific products available that can centralize data and allow everyone to access it across the organization. 2020 will be the year that companies commit to making their data more accessible to their workers as a business imperative.

  1. AI Will Continue to Spread to New Industries

Manufacturers are continuing to invest in AI solutions that address issues like preventative maintenance and the automation of certain tasks. Based on this progress, the less obvious industries will invest in this technology as well.

Verticals that are closely related to the manufacturing industry such as supply chain management and logistics are benefiting from AI applications, with logistics managers using AI applications to help forecast demand trends in key markets that can optimize their supply chains.

Companies like Amazon are also using AI-powered machines to help automate manual tasks in their warehouses. While these machines can’t complete complicated tasks, they are proving to be useful aids to workers who can pass off some repetitive and labor-intensive jobs.

On a broader scale, CISOs and security professionals are facing more complicated threats every year. With talent shortages and an overall increase in the number of IoT devices connected to any given server, companies can no longer rely on legacy or manual processes to respond to security events.

AI applications are helping to automate threat detection and can provide around-the-clock monitoring services for enterprises that are always at risk.

  1. AI Will Change The Way Work Gets Done

Much like the combustion engine or the wide-spread adoption of electricity, AI will have an impact on the way people do their jobs. More specifically, it will impact the way work gets done. AI applications will continue to enhance workers’ roles through automation and problem solving, helping to manage the burden of the millions of micro-decisions workers make in their jobs.

While the best industrial AI applications are easy and intuitive to use, the rapid adoption of AI will create specialized job opportunities. Recent reports have estimated that the adoption of AI will create 58 million more jobs than it displaces in the next few years.

There are instances where workers need to adapt to new technology, but lack the proper access to getting trained. This is where education leaders, labor organizations, local governments, and tech companies have stepped in. They are committed to the reskilling initiatives that will address the needs of workers.

  1. Companies Will Demand Accountable AI Projects

As the field of AI moves from the theoretical to the applicable, companies will demand projects that can deliver targeted results and stay on budget. According to our new report, 33% of manufacturing professionals say their company struggles with their budget scope with either being over budget or finding the resources to implement AI.

While the benefits of using AI applications at scale are clear, reaching that ROI can be a challenge for some companies. Read more about this and some of the other challenges companies are facing when implementing AI in our new report.