Akooda is using AI to help companies understand their business with fewer meetings

As organizations grow, it becomes harder to understand what’s happening operationally across departments inside a company. We tend to use meetings to try and figure out what others are doing, which isn’t terribly efficient. Akooda is an early-stage startup trying to help solve that problem by using AI to analyze the company’s internal software stack to better understand the inner workings of the organization without having to meet to figure it out — or at least meet less.

Employees can instead use generative AI to ask questions about the data Akooda is compiling. Today, the company announced an $11 million seed investment.

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

He says that the software tears this information apart, then builds it back up in a way that makes sense for individuals and managers to ask any questions they want about their organization, giving a ChatGPT kind of experience to better understand the details they might not normally have access to without a lot of tedious meetings and reporting.

While the company is using 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 the models. Instead they turn to statistical modeling and analysis to look at the customer’s unique lexicon, what they call the company’s “rare words.” Akooda analyzes each company’s own internal lingo — its acronyms, project names and customer names, he says. This helps personalize the software for each company and industry without explicitly using their data to train the models.

The next step on the product roadmap will take the software from simply answering questions to tease out information about the company and add an anomaly detection engine to surface potential problems in an automated fashion. So for example, if the software detects that a low-revenue customer is taking up a lot of internal resources, it may flag that for managers. A human could potentially find that same information if they knew to ask the right questions, but having the AI tell the manager is going to be more efficient (assuming it reports on meaningful issues).

He says this still involves 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 abstracted level, the role of the human in the loop is not going to change. We are still the conscientious decision makers, but collecting the data and putting those things on the table that will allow us to make a decision is something that is fundamentally going to change the way we manage companies,” he said.

The company currently has 16 employees and is hiring for some open roles. Gonczarowski says that he has been managing people throughout his career, and he sees diversity as a natural by-product of how you hire. “There is a very simple way to do that: you hire the best and you give everyone a fair chance and then it just happens. And that’s my leadership’s approach,” he said.

As an example he has been part of an initiative inside Israel to hire Russian and Ukrainian immigrants coming to Israel. “That is an initiative that we took an active part in from Day Zero. It’s something that we hold very near and dear to our hearts.”

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