Lambdai Space, a Milan-based fintech startup, is working with small- and mid-sized insurance companies to pilot the value of satellite images it augments with artificial intelligence.
“We are using our understanding of risk to write algorithms that make images cheaper to access, and more specific to insurance companies,” said Antonio Tinto, co-founder.
Tinto is now in Milan after working as a consultant in Hong Kong, and says the startup will market itself to insurers in Southeast Asia.
“Europe has big insurers, but the ones in Southeast Asia are dealing with a high degree of climate-change risk,” he said.
Tailored with AI
Selling images from satellites is nothing new. There are more than two dozen players around the world in the game, including Singapore’s Skymap, as well as larger players in the US.
Tinto says they are generalists or are designed for the agricultural industry. Lambdai is focused on tailoring images for insurance companies providing cover to agriculture businesses, or to financial institutions that lend to growers that can’t obtain insurance.
“Insurers are all suffering from climate change, and their processes are manual,” he said.
That customization includes using Lambdai’s proprietary AI to enhance images to identify crop failures or other problems. It is also developing large language models to provide conversational engagement, to help insurance personnel query the platform to survey the images or provide a report.
Lambdai is just getting started and is pre-revenue, but Tinto says four to six insurers are doing proofs of concept (PoCs) and says the company will be generating revenues this year. Once it has money in the bank, it can go out to do a pre-Series A fund raise.
One way to track whether those milestones are hit is whether paid PoCs are agreed before the end of June, in time to use the service before the next wave of summer storms.
Lambdai doesn’t operate its own satellites. For now it relies on open-source data from various satellite providers. This data comes with a multi-day time lapse, so it’s not suitable for anyone needing real-time insights.
Race for survival
Lambdai will have to upgrade to purchasing timely or higher-resolution data as its business evolves. It could, in theory, at some point purchase its own satellite. But for many growers, monitoring crops in the advent of extreme weather doesn’t need such immediacy.
As a young company, Lambdai’s at risk of having a rival copy its model. It is racing to develop its intellectual property, grounded in marrying affiliated data scientists’ insights with the founders’ insurance know-how. It has yet to file for any patents.
“We need to prove ourselves quickly enough for insurance companies to onboard us,” Tinto said. “After that they tend to be sticky clients.”
Tinto doesn’t have direct insurance experience but his co-founder and chief technologist, Raul Abreu, has led AI and data projects at both insurers and banks.
The company’s value proposition is more in how it treats the images, looking for impact on crops and assessing the insurance implication, rather than just selling the raw data. Its pricing structure is also different from general image vendors: instead of charging by the acre (or hectare) covered, Lambdai charges insurers and lenders based on their portfolio size.
The startup is beginning by capturing cereals: wheat, corn, rice. “We’ve researched a ton of data on rice,” Tinto said. It’s starting to measure plants (tomatoes, fruit) and could, ahem, branch into trees.
Beyond selling images to insurers and lenders, the startup hopes to monetize by selling its augmented data to commodity traders and fund managers. More immediately, though, the founders are looking for angel investors, to get some PoCs under its belt, and bring in revenues.
