There is so much more to Pinterest (PINS) than the eye can see

Millions of people use and interact with Pinterest. This interaction generates data that Pinterest can use in turn to make search better. The process is a positive feedback loop. Better data makes for better personalization, more relevance. 

To better understand the innovative ideas and projects at Pinterest, I reviewed the information at Pinterest Labs. I am a 'visual' person and like to see information mapped out as a figure or a graph, as is with much of my company assessments, I generated a unsupervised network map of projects Pinterest is involved in.

The 'engine under the hood' is involved in user modeling and recommendations this is done mostly through Machine learning algorithms to understand the users behavior as well as product/image relevance. 

Pinterest: A visual discovery, engagement, shopping and advertisement engine (click to zoom)

Pinterest is researching visual discovery. Pinterest Lens allows users to get recommendations from real world objects. The company has some of the largest datasets of visual objects. The focus is now to improve recognition and visual search. It is also looking at understanding video and moving images. Additional innovations in real world visual discovery, take search, engagement, advertisement and shopping to the next level.

With the troves of data that Pinterest generates, they are able to take a systematic approach to explore trends and track changes. This allows pinterest to be ahead of the curve so to speak in knowing what trends and tastes are evolving. This is crucial information for advertisers. Pinterest is in effect a recommendation service. The massive troves of data leads it be one of largest-scale recommender systems. A very important statement caught my eye,

"Right recommendation to the right person at the right moment"

Beside the operational side of the platform, the business side will also see significant growth. The platform is visual discovery, shopping engagement, social, search, marketing platform all in one package. Pinterest with its advanced data science, visual search analysis and a 300 billion and growing repository of human curated ideas will be able to do it! 

Disclaimer: I am an investor in Pinterest (PINS). The data were collected from publicly available sources online and from company websites.

reference: https://www.pinterestlabs.com/projects/

Uipath (PATH), a landscape of integrated technology solutions

Today we will look at Uipath in context of its integrations with other tech services. This type of visualization would be similar to ones I have done in the past for Palantir (Palantir - contract landscape), Teladoc (Business network) and even one on leadership (Crowdstrike governance). Before we being I would recommend looking to a couple minutes read into the background of network visualization, if you have not done so already. Such type of analysis allows for deep study of the companies that you are interested in investing. With that short introduction lets begin.

UiPath is an interesting company, no doubt. It is a leader in Robotic Process Automation (RPA) where repetitive tasks can be identified, and software codes can be used to automate those tasks. This is immensely helpful as one can imagine. I recall the days as a graduate student spending countless hours doing data extraction for analysis. RPA would have cut short much of that time so that more time could be focused on analysis and interpretation. This is one example of what RPA can do. So, to look at what else is RPA and specifically Uipath involved in, I looked at its integrations with other tech services. The company calls these "Technology Alliance Partners" whose task is to 'automate more within your existing technology stack'. Furthermore, UiPath natively integrates with the enterprise applications that are commonly used to extend their impact. This would an excellent clue to what other areas RPA would be useful for.

Based on the information collected from Uipath website manually (how I wish I had Uipath RPA to extract this data, they have the capacity in case you are wondering), I generated a network model of all of its technical integrations as of September 8, 2021. The graph is provided below.

UiPath Integrations with Enterprise Applications (Click on image to zoom)

The Nodes in yellow are companies that are part of the integration. The larger nodes (red through blue, in essence all non-yellow nodes) are the technologies that Uipath is integrated with these companies. 

Observations
1. There is a surprising degree of versatility seen in these integrations.Uipath shows integrations with Artificial intelligence (AI)/ Machine learning (ML) companies, Dynamic Case Management (DCM)/Business Process Management (BPM) companies [Dynamic Case Management (DCM) as name suggests is dynamic, adaptive process improvement for unstructured processes. While Business Process Management (BPM), is automating processes to automate repeatable task, reducing error and human intervention], document and text understanding, natural language processing, chatbots and digital assistants. The largest share of integration is with the infrastructure, cloud and Software as a service (SaaS) technologies. Smaller forays in other areas include analytics, test automation, Banking, security and Enterprise content management (ECM). 

2. The Cloud - SaaS - Infrastructure cluster shows 2 distinct sub-clusters, those that are on Platform side (Amazon web services, Google cloud, Microsoft etc) and those that are on the architecture side (Oracle, Citrix etc).

3. Smaller group of companies in areas such as analytics, banking, security etc.

Impressions.
I anticipate that the number of companies that integrate with the larger services  (e.g. AI/ML, Cloud, SaaS) will grow. I would however, also like to see smaller node services get more take (analytics, security and compliance) which would demonstrate the true versatility of the Uipath platform. The company has promise, and is a clear leader but it is working in a crowded space. As with some of the other companies at this time I will wait at least 3 quarters worth of earnings (so I can get a sense of revenue, growth, cash flow) to consider investing. 

Disclaimer: The above analysis is part of my personal deep dive into investing in specific companies. This is not financial advise to buy or sell securities. All of the information is publicly available on company website. I do not hold shares of Uipath (PATH) at time of this article