As companies scale, understanding operations across various departments becomes increasingly challenging. Typically, meetings are held to gain this insight, but this method isn't the most efficient. AI startup Akooda seeks to resolve this issue by analyzing a company's internal software stack to grasp the organization's internal dynamics without the need for numerous meetings. Today, the company has announced an $11 million seed investment.
Akooda's software connects to the entire digital footprint of a company, including public Slack messages, Confluence documentation, code snippets, Salesforce and HubSpot sales entries, JIRA tickets, and other knowledge-creating platforms. The software dissects this information and reconstructs it in a way that allows individuals and managers to ask any question about their organization. This provides a ChatGPT-like experience that offers details that would typically necessitate many tedious meetings and reports.
According to Akooda CEO Yuval Gonczarowski, the software uses large language models for understanding but employs a nuanced approach that avoids using a company's private data for model training. Instead, Akooda uses statistical modeling and analysis to understand a customer's unique lexicon, including acronyms, project names, and customer names. This personalizes the software for each company and industry without explicitly using their data for model training.
Looking forward, Akooda aims to develop the software from merely answering questions to identifying potential issues in an automated fashion. If the software detects an anomaly, such as a low-revenue customer consuming significant internal resources, it could alert the managers. The aim is to provide better information to human decision-makers, fundamentally changing how companies are managed.
The funding round included participation from NFX, Atlassian Ventures, Village Global, Founder Collective, and other unnamed investors. With a current workforce of 16, Akooda is actively hiring for open roles.