Founded Year



Convertible Note - III | Alive

Total Raised


Last Raised

$500K | 4 yrs ago



About Neo PLM

Neo PLM is a software company focused on Process PLM (Product Life-Cycle Management for process manufacturing). The company's flagship products include Neo Design (used to capture process definitions in a modular framework), Neo Planning (used to match process designs to available plant capacity), and Neo Analysis (used to correlate manufacturing data to process designs).

Neo PLM Headquarter Location

555 Long Wharf Dr

New Haven, Connecticut, 06511,

United States


Predict your next investment

The CB Insights tech market intelligence platform analyzes millions of data points on venture capital, startups, patents , partnerships and news mentions to help you see tomorrow's opportunities, today.

Neo PLM's Products & Differentiation

See Neo PLM's products and how their products differentiate from alternatives and competitors

  • Neo PLM Suite (different functional modules available)

    See our website:


    We are a unique, first in class solution. Nobody does what we do. Think of in discrete manufacturing (cars, aircraft, etc.) where the "CAD/CAM" 3-D graphics to look at a digital image of the vehic… 

Expert Collections containing Neo PLM

Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.

Neo PLM is included in 2 Expert Collections, including Digitization & Automation In Manufacturing.


Digitization & Automation In Manufacturing

74 items


Advanced Manufacturing

3,328 items

Companies focused on the technologies to increase manufacturing productivity, ranging from automation & robotics to AR/VR to factory analytics & AI, plus many more.

Neo PLM Patents

Neo PLM has filed 2 patents.

The 3 most popular patent topics include:

  • Manufacturing
  • Pharmaceutical industry
  • Process management
patents chart

Application Date

Grant Date


Related Topics




Production and manufacturing, Product lifecycle management, Manufacturing, Pharmaceutical industry, Process management


Application Date


Grant Date



Related Topics

Production and manufacturing, Product lifecycle management, Manufacturing, Pharmaceutical industry, Process management



Latest Neo PLM News

Digital transformation delayed

Dec 12, 2019

Digital transformation delayed By Cathal Strain President, Neo PLM Dec 12, 2019 The manufacturing world is currently dominated by buzzwords such as “digital transformation,” “industrial internet of things” and “Industry 4.0.” Not to be left behind, pharmaceutical companies have begun using the same terminology — including the discussion of “Pharma 4.0.” At the same time, however, critical business processes in pharma remain heavily dominated by a document-centric paradigm. Even worse, most manufacturing records are still paper-based. This dichotomy raises the question: Is the pharma industry truly ready for digital transformation? The “Pharma 4.0” hype is largely being driven by the software industry that has served pharmaceutical manufacturers for the past three to four decades. Yet these same vendors have failed to meet a fundamental challenge facing the industry since the late 1980s: moving to a paperless, data-driven manufacturing environment. In other words, pharma has not yet achieved “Pharma 3.0 “objectives. The stock explanation for this delay is to point the finger at the stringent regulatory environment surrounding pharmaceuticals. But shouldn’t the software industry shoulder some of the blame? Vendors could be driving innovation-based strategies, helping to automate compliance and empower agile business processes across the product lifecycle. Instead, they have simply facilitated labor-intensive, document-centric approaches. This model has not been without its benefits for software providers. Leveraging Big Pharma’s substantial financial resources and desire to meet industry compliance requirements — sometimes at any cost — software providers have generated significant licensing and services revenues. Meanwhile, technology stagnation has negatively impacted pharma in multiple ways. As ongoing innovation drives new technologies to evolve, they tend to become less expensive, easier to use, and, ultimately, accessible to everyone. Pharma manufacturers have not experienced this phenomenon, particularly on the shop floor, where process automation is still applied haphazardly. Few companies have achieved the promise of end-to-end, recipe-driven automation. As for adoption of manufacturing execution systems (MES), the continued prevalence of paper-based manufacturing records speaks volumes. In fact, the use of information systems in pharma has not changed significantly since the 1980s. The typical technology stack consists of enterprise resource planning (ERP), MES, a process control system (PCS), a laboratory information management system (LIMS) and a process historian. Other solutions include warehouse management, corrective and preventative action (CAPA) and document management. This may sound like a reasonably complete package in terms of functionality. However, the reality is that these technologies don’t come close to delivering the integrated, data-driven business environment envisaged in a digitally transformed world. This same stack has existed for three decades. Digital transformation requires radically new thinking for pharmaceutical manufacturers, and a 30-year-old technology stack is unlikely to be up to the task. So how much should we fault technology providers themselves? Genuine innovation is user-driven. If software companies don’t receive insightful customer feedback, it is unfair to assign them all the blame. However, poor user input alone doesn’t explain the lack of innovation. The fact remains that software vendors are not providing solutions that are progressively more functional, easier to use and less expensive. On the contrary, the costs associated with deploying the conventional stack described above are generally growing. Again, this has been chalked up to increasing regulatory demands. As for availability to everyone, large segments of the pharma supply chain are still not using MES or PCS. They are simply too expensive to buy, deploy and support in a multi-product manufacturing environment. Innovation over the past 30 years should have made these technologies universally accessible — then the industry would be ready for true digital transformation  Related Content

  • When was Neo PLM founded?

    Neo PLM was founded in 2011.

  • Where is Neo PLM's headquarters?

    Neo PLM's headquarters is located at 555 Long Wharf Dr, New Haven.

  • What is Neo PLM's latest funding round?

    Neo PLM's latest funding round is Convertible Note - III.

  • How much did Neo PLM raise?

    Neo PLM raised a total of $1.05M.

  • Who are Neo PLM's competitors?

    Competitors of Neo PLM include Fluxa, Seebo, Canvass Analytics, MoBagel, Instrumental, SparkCognition, Uptake, Seeq, Falkonry, Plex Systems and 14 more.

  • What products does Neo PLM offer?

    Neo PLM's products include Neo PLM Suite (different functional modules available).

You May Also Like

Canvass Analytics Logo
Canvass Analytics

Canvass Analytics is a software provider of AI industrial advanced analytics. Canvass's patent-pending platform enables intelligent industrial operations by putting AI in the hands of plant operators, empowering them with data-driven insights to improve complex operational processes and optimize assets. Developed for the industrial sector, Canvass's AI utilizes machine learning to continuously adapt to operational variables, spearheading industrial operators to increase yield, improve quality, and lower energy consumption. The company was founded in 2016 and is based in Toronto, Canada.

SparkCognition Logo

SparkCognition builds AI solutions for applications in energy, oil and gas, manufacturing, finance, aerospace, defense, and security. SparkCognition's products include Darwin for automated model building, DeepArmor for AI-built cybersecurity, SparkPredict, an analytics solution, and DeepLNP, a natural language processing solution.

RapidMiner Logo

RapidMiner, formerly Rapid-I, is redefining how business analysts use Big Data to predict the future. With an open source heritage, RapidMiner is one of today's most widely known and used predictive analytics platforms, providing powerful solutions for a wide variety of industries.

Savi Technology Logo
Savi Technology

Savi delivers live, streaming facts and insights about the location, condition, and security of in-transit goods. Using big data and analytics, Savi equips shippers, carriers, 3PLs, and governments with insights to optimize supply chain logistics before, during and after transit, reducing costs and inventory while improving service.

Sight Machine Logo
Sight Machine

Sight Machine provides manufacturing analytics to make better, faster decisions about their operations. Sight Machine's analytics platform, purpose-built for discrete and process manufacturing, uses artificial intelligence, machine learning, and advanced analytics to help address critical challenges in quality and productivity throughout the enterprise. The platform delivers "AI for the plant floor" and is powered by the Plant Digital Twin, which enables real-time visibility and insights for every machine, line, and plant throughout an enterprise.

Instrumental Logo

Instrumental offers a testing platform to manufacturers of electronics, to head off complicated problems before they start costing companies thousands of dollars per minute.

Discover the right solution for your team

The CB Insights tech market intelligence platform analyzes millions of data points on vendors, products, partnerships, and patents to help your team find their next technology solution.

Request a demo

CBI websites generally use certain cookies to enable better interactions with our sites and services. Use of these cookies, which may be stored on your device, permits us to improve and customize your experience. You can read more about your cookie choices at our privacy policy here. By continuing to use this site you are consenting to these choices.