A theme emerged in which all a startup needed to do was announce its intention to address it — and immediately raise investments 😉 At least, this startup managed to raise $3.8 million. This theme is AI decision-making platforms, which are intended to replace old business analytics platforms.
Because analytics itself has no inherent value. Value lies solely in the decisions made by people based on this data. But in many cases, people can already be replaced by AI! And this opens the way for the creation of a new generation of platforms.
The catch is that even the market for old business analytics platforms is a significant $30 billion, expected to double in the coming years. But if a new generation of platforms enters this market, it could grow even larger!
This means that now is the time to enter with your own platform. But first, you need to understand what is in demand here and what earns money:
Project Essence:
Writ was created recently, and its website currently only has a placeholder consisting of a few paragraphs of text. Yet it has already raised its first $3.8 million in investments, which made me wonder what it did to attract funding and why.
The startup is building a platform for business analytics — “what it should be.”
Both in the past and today, special attention has been given to how companies can use their available data to create competitive advantages. Although AI has emerged, many companies still make decisions the same way they did decades ago — using the same business analytics tools and platforms.
All “old” business analytics essentially consist of dashboards. However, dashboards alone do not create any value. The value is created by people who look at these dashboards and draw their own conclusions.
The situation is changing incredibly fast nowadays — so looking at dashboards and drawing conclusions needs to be done very often. It is not always necessary to start from scratch, as new solutions can benefit from information on what old solutions were based on and how decisions were made using that data. AI can help with all of this.
Here are a couple more paragraphs from another source.
Writ’s concept is very simple — it’s a system for creating and using dashboards in the era of AI:
Firstly, it should work “proactively” — suggesting possible solutions and actions that different departments of the company need to take. Secondly, it should show information about the decisions made based on the data presented by the system, and what results these decisions led to. Classic dashboards are purely a communication tool, capable only of displaying data. Therefore, the question and task are about how to apply AI to create a new generation of dashboards — ones that shorten the path to making decisions based on this data.
What’s Interesting:
A couple of months ago, I noticed a post on Twitter that said: “An initially non-obvious thing I realized while creating a dashboard for top management — they don’t need dashboards at all! When I showed them dashboards with lots of charts, switches, and filters, they didn’t understand where to look and what to do with them. Because they wanted to see ready-made insights presented in the simplest way possible.”
Inspired by this phrase, I wrote a whole post about products in general — with the message that “the user doesn’t want to solve anything, they want handles” 😉
But in this case, there’s no need to generalize anything. Because this tweet hits the same point that today’s Writ is aimed at — making the next qualitative step in the development of business analytics platforms by transitioning from actual business analytics systems to decision support systems based on data.
In principle, such decision support systems already exist somewhere and for someone — but they are currently complex and expensive. However, AI can make such systems simple, accessible, and mass-produced.
This idea is already in the air, so other startups are already moving in this direction.
Last fall, I wrote about Flawless, a startup that made a platform that allowed company employees to “pay less attention to dashboards” — because the platform analyzed them itself and notified the necessary employees of any abnormal situations.
This startup raised $3.2 million in investments but has now rebranded to Eversync and prioritized full automation of business processes — which essentially is the same automated decision-making system based on data. After all, the platform attracts people to make decisions only in cases of abnormal situations and when human intelligence and manual actions are needed.
Triple Whale, a startup I wrote about a year ago, made a decision support platform based on data for e-commerce businesses, and they’ve already raised $52.7 million for it.
Fora, which I wrote about in February, made an AI assistant for top managers of companies, and its task is the same — to shorten the path from data analysis to decision-making. The startup’s offer is to “spend 30 seconds making a decision instead of 30 minutes studying the problem.” This startup raised $3.8 million in investments.
An unexpected application of the same approach can be seen in Astronuts, a startup I wrote about recently. Their platform tracks the efficiency metrics of developer teams’ work — however, its main value is in providing insights into what and with which AI tools team members can change in their work to improve these metrics. And the corresponding AI tools are also part of their platform 😉 This startup was created recently and is currently only going through the Techstars accelerator, so it cannot boast of large investments yet.
Where to Run
The general direction of movement is towards creating simple, accessible, and mass-produced decision-making systems based on AI technologies that can replace traditional business analytics systems.
The trick is that the market for business analytics platforms is already large. Its size in 2023 was almost $30 billion. It was expected to double by 2032 — reaching $55 billion.
However, it is not excluded that it will grow even larger precisely due to the arrival of a new generation of platforms — not only simpler and more accessible but also more efficient, as they will leap from simple data analysis to decision-making.
It seems that I am not the only one who thinks so. Otherwise, today’s Writ would not have raised investments simply by announcing that it intends to move in this direction 😉
In what area can you replace traditional business analytics platforms with decision support platforms? What data are currently being analyzed by such platforms? What decisions do people make based on this data? Which of these decisions can be automated using new AI technologies? Can, as a result, the corresponding business processes be fully automated? How to distinguish routine situations that can be processed automatically from abnormal ones, in which decisions must be made by people?
About the Company:
Writ Website: writ.so
Last Round: $3.8M, April 11, 2024
Total Investments: $3.8M, Rounds: 1