Meet UTU, A Nairobi-Based Startup That’s Solving Human ‘Trust Issues’ With Machine Learning
Machine learning is reaching many parts of human life. As exploration deepens many more applications are being discovered. One of the newest application of artificial intelligence and machine learning comes in the field of trust. UTU, a Nairobi-based startup is now serving personalised recommendations for trusted service providers on sharing platforms. It is used to drive conversion, satisfaction, retention and viral acquisition. In a conversation with Analytics India Magazine Jason Eisen, CEO of UTU Technologies described their startup as: “An ML-powered recommendations engine based on a real human model of trust, that does not try to prescribe trust between individuals but rather to describe, in human terms, why two people may trust each other based on their relationships, past experience, and various contextual factors.” Eisen explained how UTU started as an “accident”. He shared, “We started UTU on accident, I suppose. Back in the very early days of taxi apps and e-hailing, we started a taxi app in Nairobi, Kenya called MARAMOJA. We realised that the problem to be solved in Nairobi was not about just finding a taxi, but critically, finding a trusted taxi. We built a primitive version of what would become our trust engine to amazing results. It drove huge increases in conversion rates, customer satisfaction, retention, and other key metrics. It made our network of driver partners feel empowered to build their own clientele under our umbrella and to date has kept our riders 100 percent safe in a city with a complicated crime problem.” UTU currently offers several trust services to their clients. The services include Family Services where can drive trust on clients platform for needs like hiring a babysitter or a nanny. Other important services include peer-to-peer lending use case and P2P commerce. Eisen says, “The early success of our trust engine got us questioning why all of the digital infrastructures around building trust on marketplaces and online platforms, have nothing to do with this simple fact about how people trust. We believe that there’s no such thing as a prescriptive model for trust that can tell us who we should trust. As people, we already know who we trust.” UTU maybe is the only startup which is a pioneer in a new class of service called Trust Infrastructure as a Service (TIaaS). Eisen says that soon the service will be available as an API and suite of smart contracts for sharing economy platforms and digital marketplaces to leverage for better trust in their communities. When asked about how their journey has been so far, Eisen simply said, “The journey for us has been long and winding.” The UTU story started five years ago with a mobility app. Since then, UTU has signed contracts around Africa to expand the mobility business across the continent. They have been accepted into prestigious programs like SeedStars Global, Zeroth.AI, and AEternity Starfleet. Most recently they have been able to raise venture capital from a global investor to fuel the development of their trust engine for other sectors of the sharing economy. The startup is currently working on two products. The first product is a locally customisable franchise solution for e-hailing. It has been taken up by local entrepreneurs around Africa seeking to have a world-class e-hailing app that they can take to market quickly and cheaply. The second product, about which the team are deeply excited, is the trust engine as a stand-alone service. The team is actively soliciting pilot partners across all sectors of the sharing economy for custom adaptations of trust engine and API, built to fit their use case and needs. UTU will be delivering UI components and other features to make integration of the trust engine as simple as possible. UTU is heavily human-focussed and loves to interact with the customers. Eisen says, “Most of our competitors tend to think about trust from a data-centric perspective, rather than a human-centric one. They model trust as ubiquitous, monolithic, static, and purely transactional. Furthermore, many try to productise that trust in consumer-facing platforms that invariably lose credibility with scale. Their products are built for everybody, meaning they’re ultimately built for nobody.” The future of UTU seems bright as Eisen adds, “We’re deepening and extending our ability to make contextually aware trust recommendations, building platform integrations for both traditional and decentralised applications, and working on a consumer-facing product to offer people a safe refuge for their data, let them identify trusted service providers and sellers on any platform they use, and to monetise their endorsements of good service providers in the blockchain protocol we’re developing to tokenise trust.” The team at UTU is hard at work to solve trust. Eisen previously led strategy, design, and development of large-scale projects across multiple sectors and helped secure more than $3 billion in funding and funding opportunities for his employers and clients. Dr Bastian Blankenburg is an important member of the core team as he is one of the founders as well as the CTO. He brings academic experience in trust and industry experience in transportation technology. Polina Kazak is a founder and works as the creative director at UTU and brings over 14 years experience of designing emotive, user-centred apps and sites for startups and multinationals across Russia, Europe, and Africa.
Machine learning is reaching many parts of human life. As exploration deepens many more applications are being discovered. One of the newest application of artificial intelligence and machine learning comes in the field of trust. UTU, a Nairobi-based startup is now serving personalised recommendations for trusted service providers on sharing platforms. It is used to […]
UTU, a Nairobi-based AI startup is now serving personalised recommendations for trusted service providers on sharing platforms. It is used to drive conversion, satisfaction, retention and viral acquisition.
["Startups"]
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["AI", "artificial intelligence", "machine learning", "ML", "analytics", "RAG", "R", "Go", "Rust", "Git"]
As a thorough data geek, most of Abhijeet's day is spent in building and writing about intelligent systems. He also has deep interests in philosophy, economics and literature.