Periodic Reporting for period 1 - ellpha.ioWomenEUTech (ellpha.io: accelerate bias tackle and commercial footprint)
Période du rapport: 2023-07-01 au 2024-06-30
Stephanie Creff and Brigitte Ricou Bellan have a bold Purpose-driven Vision - They believe diversity is good for the world, good for business, and good for the soul. New models, applications, powered by AI, can be directed at the world’s biggest issues and can help create awareness, take action and accelerate change.
Ellpha wants to tackle bias & noise in talent management to step-change diversity in companies’ businesses. Increasing diversity is a burning platform for enterprises and societies, driven by Ethics and Compliance. Governments, companies and societies are truly committed to accelerating Diversity, Inclusion, Equity & Belonging (DEIB), but they lack data & insights to spark changes and accelerate DEI. This is where Ellpha smart technology comes in.
Ellpha is a Social Science model designed into an AI: the Bias Detection EngineTM. It offers unprecedented ability to uncover and surface hidden bias & stereotypes in real time and across growing data sets. Ellpha Bias Detection EngineTM is able to understand complex notions such as a talent’s agency, impact, perceived leadership or the specificity of a future career path. Indeed, Ellpha innovative software detects and corrects bias at an individual & collective level, in business context, a domain which remains largely unexplored.
At the beginning of the project, Ellpha had developed smart technology to spark action. The team had built an AI solution, with a Bias Detection EngineTM which can be applied to existing corpus of HR/Corporate content sets as well as an award winning end2end SaaS solution Talentuum.io . (Find out more on Talentuum.io here .) Its challenge over the next few years was relying on deepening its high-tech solution (considered bias, personalization, recommendations, integrations) and accelerating its commercial development and business opportunities through overcoming some of its clients’ challenges.
The women Tech EU program was supposed to support Ellpha by:
● Contributing to the funding of the R&D (enhancing the model on all dimension of diversity) and commercial development of the company
● In terms of mentoring and coaching, Ellpha’s founders expected to benefit from help about the best way to make their offer and value proposition easily understandable and accessible to key decision makers in clients’ organisations.
In this context, Ellpha got many achievements thanks to this program.
In terms of commercial development of the company, Ellpha worked as expected on the design, development and production of a simple, web-based on-boarding and trial package “ELF” .
In Terms of R&D, Ellpha wanted to develop tools which could help the company to facilitate the onboarding of the clients. The way identified when the project was submitted was to integrate the Talentuum with workday, among the most used HR Platform, beyond Ellpha’s prospect. This would have enabled the company to collect data and make a demonstration of its solution directly based on its prospect data. This strategy faced difficulties related to personal data. Its prospects were reluctant to give access to their employee’s personal data.
In order to bypass this problem, Ellpha developed a tool based on generative AI, which enable to extract meaningful data in a text without personal data. This change of path drives the same result as expected, with a solution more respectful of personal data and aligned with broad data privacy concerns and regulations.
The stand-alone trial product based on Ellpha’s bias detection engine - ELF - is functional. A demo version is available, all communication and teaching material can be used for commercial outreach and conversion of prospective clients which is our priority. While we were creating our demo product, a lot of work was also going on to step-change our bias detection model and build a new back end based on LLMs. This new approach works well on a text without needing to know personal data about the individual. However, it required a re-evaluation of the user workflow in ELF.
As a result, we have deprioritised the integration of Talentuum with Workday and invested in this extra work on the user workflow as well as on some extra commercial efforts.
We believe that the fact that we won’t need to use (and therefore export and manipulate) personal data in the future has overcome another barrier to adoption.