Koios is a voice-driven AI platform on a mission to fundamentally improve the way that organisations work with their talent. Aiming to provide talent leaders and organisations with bespoke ways to communicate, motivate and develop each employee, we are developing and applying state-of-the-art audio deep learning models using original data collection with an emphasis on a conscientious and ethical approach.
Our story began in 2020 when our founders, Tom and Alex, experienced first-hand the insatiable hunger for better understanding of their talent in the workplace during their time at Spotify and AI & Elements. Witnessing the limitations of traditional self-assessments, they knew there had to be a better way. That's when Dr. Martin Lukac joined the founding team, bringing with him pioneering expertise in Computational Social Science.
Driven by their shared passion for innovation, the Koios team embarked on a journey to solve this problem by harnessing the power of AI. Martin quickly spearheaded the development of our revolutionary model - the ability to predict an individual's Big 5 personality score purely from the acoustic signal of their voice. This breakthrough has eliminated the need for cumbersome self-assessment methods, making the process efficient, cost-effective, and insightful.
We understand the increasing challenges faced by leaders managing distributed workforces and the need to deeply understand their people. Traditional personality assessments fall short in this dynamic environment. At Koios, we believe in democratising access to high-quality personality and management insights, enabling leaders and organisations to have a bespoke approach to talent management and development based on each individual's unique personality.
With our cutting-edge technology, Talent and HR leaders can now unlock the untapped potential within their teams. We provide a seamless and engaging experience, allowing leaders to gain valuable insights into the inner workings of their talent, drive meaningful connections, and make informed decisions that fuel success.
Tom Sherwood
Co-Founder/CEO
After spending 5 years in the British Army and completing operational tours of Iraq & Afghanistan, Tom started his career in Talent & Recruitment in early 2011. Now with over 10 years of experience working at the likes of Robert Half, Apple, Spotify & Snapchat where he most recently led sales hiring across EMEA & Asia. Outside of work you’ll find him either on the golf course or frantically running around after his three children.
Alex Lewis
Co-Founder/COO
Alex has spent a decade working in the Talent & People space, focusing on startups and corporate innovation across Europe, ME and SEA. Most recently he was working with Seedcamp, serving a portfolio of 450 companies from Pre-Seed to Series A, helping founders with hiring and people strategy, GTM, leadership and venture growth. Outside of work he is a fan of fitness, rugby, skiing and tennis, country pursuits and his dog, Bertie.
Dr. Martin Lukac
Co-Founder/ Chief Data Scientist
A distinguished computational social scientist and Chief Data Scientist with over a decade of experience, Martin has expertise spanning machine learning & AI, agent-based modelling, and social science research methodologies. Holding notable positions at QuantCo, the London School of Economics, and the University of Oxford, Martin pioneered innovative audio deep learning models and spearheaded the ethics behind Koios’ technology.
Dr. Samina Shaheem
Head of Behavioural Psychology
For the past 25 years, Samineh has been a Professor of Cross-Cultural Psychology and Managing Consultant in Learning and Development. She was also the Dean and Executive Director of Hult International Business School for 6 years. She believes in 'learning more to live more'. Even while relaxing, she's constantly observing and learning, aiming to enhance human experience. To recharge, she travels with loved ones, indulging in new sights and sounds for mental refreshment.
Applying deep learning and organisational psychology to unleash human potential.
