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Akooda Uses Artificial Intelligence to Help Businesses Understand Their Business with Fewer Meetings | TechCrunch

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As organizations grow, it becomes more difficult to understand what is happening operationally between departments within a company. We tend to use meetings to try and understand what other people are doing, which isn’t very efficient. Akooda is an early stage startup looking to help solve this problem by using AI to analyze the company’s internal software stack to better understand the internal workings of the organization without having to meet to figure it out or at least meet less.

Instead, employees can use the Generative AI to ask questions about the data Akooda is compiling. Today, the company announced an initial investment of $11 million.

Akooda CEO Yuval Gonczarowski says his company looks at the SaaS tools running within an organization and builds a picture of what is happening operationally within the company. We connect to your organization’s entire public digital footprint, including public Slack messages, Confluence documentation, snippets of code, sales entries in Salesforce and HubSpot, JIRA tickets, anything where knowledge is created in the enterprise, Gonczarowski told TechCrunch.

He says the software tears this information apart, then reconstructs it in a way that makes sense for individuals and managers to ask all the questions they want about their organization, offering a ChatGPT type of experience to better understand details they might not normally have access to without a lot of tedious meetings and reports.

While the company uses large language models to achieve this level of understanding, Gonczarowski says it’s more nuanced than that because he doesn’t want to use a company’s private data to train models. Instead they turn to modeling and statistical analysis to examine customers’ unique lexicon, what they call the company’s rare words. Akooda analyzes each company’s internal jargon, its acronyms, project names and client names, he says. This helps tailor the software for each company and industry without explicitly using their data to train models.

The next step in the product roadmap will require the software to simply answer questions to extract business insights and add an anomaly detection engine to surface potential issues in an automated way. So, for example, if the software detects that a low-income customer is tying up a lot of internal resources, it could alert managers. A human could potentially find the same information if he knew to ask the right questions, but having the AI ‚Äč‚Äčtell the manager will be more efficient (assuming he reports significant issues).

He says this still engages human decision-makers, but it’s giving them better information on which to base their decisions. If I look at things from a more theoretical level, an abstract level, the role of the human being in the world won’t change. We are still the conscientious decision makers, but gathering data and putting those things on the table that will enable us to make a decision is something that will fundamentally change the way we run businesses, she said.

The company currently has 16 employees and is hiring for some open positions. Gonczarowski says he’s managed people throughout his career and sees diversity as a natural byproduct of the way he hires. There’s a very simple way to do this: hire the best and give everyone a fair chance and then it just happens. And that’s my leadership’s approach, he said.

For example, it took part in an initiative inside Israel to hire Russian and Ukrainian immigrants coming to Israel. This is an initiative in which we have taken an active part since Day Zero. It is something we hold very near and dear to our hearts.

Today’s investment came from a variety of companies including NFX, Atlassian Ventures, Village Global and Founder Collective, as well as other unnamed angels.



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