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Barry Lane

Head of Product Strategy

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Peak named in 2022 Gartner® Market Guide for Multipersona Data Science and Machine Learning Platforms 

By Barry Lane on June 14, 2022 - 10 Minute Read

We are well and truly in the Intelligence Era. The adoption of artificial intelligence (AI) is accelerating at lightning speed, 90% of businesses now use or plan to use AI. Widespread AI adoption will require stakeholders from across a business to engage with and support AI development.

This need is giving rise to a new type of platform – one that brings together multiple personas to collaborate on AI builds and utilize AI applications. It’s our vision to put Decision Intelligence into the hands of everyone within a business, from data engineers and data scientists, through to commercial users.

Peak is delighted to be listed as a Representative Vendor in this 2022 Gartner Market Guide report. 

What is a multipersona DSML platform?

Gartner describes the multipersona DSML platform as:

“A cohesive and composable portfolio of products and capabilities, offering augmented and automated support to a diversity of user types and their collaboration. The primary aim of “multipersona DSML platforms” is to create value through democratization.”

Democratization, Gartner states, “is achieved by bringing the power of DSML to a wider nontechnical and technical audience while hiding complexity “under the hood” by automation and augmentation throughout all phases in the DSML development and operationalization process.” The report further states, “Multipersona DSML platforms have dual-mode characteristics: first, they offer a low-code/no-code user experience to personas that have little or no background in digital technology or expert data science, but who typically have significant subject matter expertise or business domain knowledge. Second, these platforms provide support to more technical personas (typically expert data scientists or data engineers). Nontechnical personas are provided access through a multimodal user interface that offers at least a visual workflow “drag-and-drop” mode and optionally a higher-level guided “step-by-step” mode”.

The vast majority of AI models still fail to be productionized, and accelerating time to value for AI projects is increasingly a priority for businesses already heavily invested in the technology. 

Gartner reports that multipersona DSML platforms enable acceleration, which allows companies to shorten the time to value for DSML, primarily through “more streamlined deployment, integration and operationalization of models.” 

It is Peak’s view that multipersona DSML platforms address many of the challenges faced by businesses looking to deploy AI. By simplifying, and speeding up, the development and productionization of models, the likelihood of value being realized from the adoption of AI is increased. 

It’s not just about building and deploying models, it’s about delivering outcomes from them.

“Even with the rise of the multipersona DSML platforms, there’s still a tendency for platforms to be heavily weighted towards the needs of data scientists and data engineers,” says Richard Potter, Peak’s CEO. “We believe in delivering tangible business outcomes, and for that, business users need to be brought into the conversation and onto the platform.”

Just helping data scientists to build models is not enough. It creates both a technological and cultural gap between data science teams and business users that can be difficult to overcome. There needs to be an environment where the two groups can collaborate to build effective models, ultimately transforming into critical business applications, without the complexity of stitching together an array of disparate technologies.

Peak solves this problem by offering a suite of configurable AI and Decision Intelligence applications, on top of the DSML functionality, aimed at delivering AI-driven outcomes in commercial decision making. It is in this way that we’re able to support business users, alongside data and analytics personas, to deliver tangible results.

Marshalls are turbocharging digital transformation with Peak

Marshalls is the UK’s leading hard landscaping manufacturer of natural stone and innovative concrete products for the construction, home improvement, and landscape markets. They came to Peak with a clear objective to improve efficiency within their bid process but first needed to unify their data and build the necessary infrastructure to successfully deploy AI. 

Peak collaborated with Marshall’s technical and commercial teams to train and deploy an application that integrated with commercial decision makers’ workflows, enabling line of business users to interact with the model on Peak, speed up the sales cycle and increase the volume of sales. Uniting all teams on one platform means that applications are built with an outcome and end user in mind, and creates a feedback loop between technical and commercial users, so models can be iterated and improved.

When asked about the impact of connecting their teams through our multipersona DSML platform Marshall stated it had “turbocharged” their digital transformation. 



Optimizing pricing and processes to keep customers happy.

“There is a new discipline emerging within data science, one that is outcome focused – where models are built to deliver on a stated business need and routinely deployed. This outcome focused approach is the key to the commercial adoption of AI. The rise of multipersona DSML platforms, particularly those focused on business outcomes, will be key to making this happen.”

Richard Potter

CEO, Peak

*Gartner, “Market Guide for Multipersona Data Science and Machine Learning Platforms”, Pieter den Hamer, Carlie Idoine, et al., May 2, 2022.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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