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Sindio: Predictive Infrastructure Stress-Testing for Densifying Cities
ProposalGrant
Closes November 18th, 2026$0raised
$20,000minimum funding
$20,000funding goal
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42 daysleft to contribute
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Project summary
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.
What are this project's goals? How will you achieve them?
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
How will this funding be used?
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.
Who is on your team? What's your track record on similar projects?
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.
What are the most likely causes and outcomes if this project fails?
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
How much money have you raised in the last 12 months, and from where?
None, I've bootstrapped the startup for the last 18 months