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I'm building Sindio. Sindio is a vertically-integrated, physics-informed brain for the physical city that makes city infrastructure predictable, pin-pointable, and adaptively scalable, for dense & densifying cities, with a multi-model foundation model. Sindio separates recurring seasonal stress from density-driven structural stress across eight infrastructure types, then pinpoints exactly where to intervene. Operators get spatially explicit alerts,. cascade simulations, and ROI evaluators that quantify upgrade payback. Sindio is reliant, for data, on MFOSC, discrete FBG, Vernier FBG, and MEMS FP
Sindio is currently fully operational and live in Nairobi: 29K+ assets, 18mo history, 87% recurring detection. Nairobi Water & NMS in discussion. Sindio will eventually scale to other dense/densifying cities across the world.
My goal with this project is to make city infrastructure predictable before it fails, so that dense, densifying cities can see which of their power, water, road, transit, and waste assets are under density-driven strain, not just seasonal stress, and intervene where it pays
I am to achieve this with the aid of a multi-model foundation model that separates recurring seasonal stress from structural strain, then outputs spatially explicit alerts, cascade simulations, and ROI evaluators for upgrades. Proven live in Nairobi: 29,000+ assets, 18 months of history, 87% detection accuracy — then scaled city by city
I'll use it for building the first MFOSC prototype, hiring a CTO so that the founder is not the bus factor, signing a data licensing MOU with 1 utility, adding a a former regulator to the advisory board.
The team is currently made up of 4 people.
One of them, the founder, Jordan Mafumbo, is a civil engineer with over 7 years experience in high-rise design, and urban planning across South Africa, East Africa, and Europe. He holds fellowships with IRCICA, Emergent Ventures, SPAB. Holds membership positions with INTBAU, The Georgian Group, The Commonwealth Heritage Forum. Writes extensively (articles and research papers) on infrastructure-adjacent urbanism in the region: domestic connectivity, inclusive urban planning, AI-based flood prediction, transport corridor pressure, across Kenya, Ethiopia, and Uganda
The second is Amina Wanjiku, a geospatial data scientist with expertise in urban morphology and infrastructure resilience modelling. Specialises in integrating GIS datasets with machine learning pipelines for predictive urban planning. Previously contributed to the Nairobi Integrated Urban Development Master Plan and the Lamu Port-South Sudan-Ethiopia Transport Corridor assessment
The other two are technical devs that would prefer anonymity.
The causes could include: data stays siloed so it won't transfer beyond Nairobi; no paying buyer before procurement runs out; generalisation drift in new cities
The outcomes could include: open-sourced pipelines/data become reusable public goods; a published negative result; low counterfactual cost
None, I've bootstrapped the startup for the last 18 months
There are no bids on this project.