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Most entity management system implementations fail to meet the project goals (96%). The primary reason they fail (72% of the time) is because teams struggle to keep the software up to date over time with the large amount of data entry required to build and maintain a single source of truth for entities.1 The accuracy of data in business software systems has a natural decay rate of 20-30% per year. Without teams maintaining the data through repetitive data entry and admin work, the usefulness of an entity management system will decay rapidly as the data loses currency.
As complexity has surged in recent years for managing business structures driven by ESG trends such as ultimate beneficial ownership (UBO) reporting and Pillar-2 global minimum tax, legal and finance teams are under increasing pressure to maintain accurate sources of truth for entities to support business goals.
However, most teams need help with competing priorities and bandwidth to maintain an accurate single source of truth for entity structures to meet these expanding requirements. The natural state of data in subsidiary governance is unstructured as new information is produced in text documents such as board consents and agreements. As the scale of unstructured data builds, information silos, costs, and risk all compound unless more human effort is applied to manually update data.
Athennian AI is a Generative Artificial Intelligence (GenAI) agent designed specifically to scale records maintenance for complex business structures starting with automated data entry. Athennian AI materially reduces the barrier to entry for legal, finance, and business teams seeking to create a single source of truth for entities without having to linearly increase human input.
Our design strategy for Athennian AI is to focus on discrete activities that Athennian users execute everyday. These activities are being re-imagined with GenAI and bundled into specific capabilities that we call Skills.
Our first Athennian AI Skill is Centralize. Centralize accelerates the filing and tagging of documents in the right entity profile, folder hierarchy, and with the correct metadata such as effective dates and descriptions. According to surveys of our customers, getting documents into the right place and tagged appropriately consumes approximately 20% of primary users' time. With Centralize that is reduced by 90% to 2% of primary user time. Our average customer will save over 120 hours or 7 days per year of team time with Centralize.
Centralize accepts documents via browser upload as usual. However, we are also opening up a new off-browser engagement channel with Athennian AI: email. Each customer will have a unique email address (e.x., acme@athennian) that they can share with their internal and external teams to send or copy attached documents to be filed without having to log-in.
Centralize can handle a range of PDF and image document types successfully. We tested documents in a variety of languages, including Hebrew and Japanese for non-Latin characters. Handwritten documents are supported, coming from very old entities or jurisdictions where handwritten documents are still customary. Athennian AI can also read low-quality document images by scanning them.
We believe our strategy of focusing on discrete activities with thoughtful design and not trying to boil the ocean with ChatGPT wrappers achieves several outcomes:
1. Skills that automate specific activities are easier for users to integrate into their workflow
2. Lower risk of losing trust with users via hallucinations that come from generic chat-bot experiences
3. Easier for business leaders to quantify and report ROI from AI to justify investments
Data in an entity management process has three stages: create the single source of truth by centralizing data in one place; automating existing processes such as report generation; and integrating the data into business processes such as board meetings, investor reporting, regulatory filings, etc.
In the near term, we will focus Athennian AI on accelerating the Create stage where teams are trying to build and maintain a single source of truth for entities. In time, we will shift our focus to the Automate and Integrate phases with tools to automate processes such as requests for information in KYB and audit processes.
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