“Revolutionizing Banking: Hyperplane’s Mission to Implement AI”

The general idea here is to help banks use their first-party data to build personalized experiences by predicting user behavior. The company is already working with about a dozen banks in Brazil and has not set its sights on expanding to the U.S. as well. And while Hyperplane is currently solely focused on the world of banking, over time, the team plans to bring its technology to other verticals, too. At its core, Hyperplane provides these banks with the APIs to build these personalization models on the fly. “The Hyperplane Cloud can scale across markets with little effort, and we”ll soon announce our first partnerships in the U.S.”

Hyperplane, a San Francisco-based startup that is building foundation models to help banks predict customer behavior, is emerging today with a bang after securing a $6 million funding round. The round was led by former Stripe exec Lachy Groom, joined by a group of prominent investors including SV Angel, Clocktower Technology Ventures, Liquid2 Ventures, Soma Capital, Latitud, Atman Capital, Crestone VC, and Norte.

This particular startup has an interesting premise – assisting banks in utilizing their first-party data to construct personalized experiences by accurately predicting user behaviors. With already about a dozen banks in Brazil under its belt, this company is now looking to expand to the U.S. market.

Although Hyperplane’s focus is currently on the banking sector, their long-term goal is to bring their innovative technology to various other industries as well.

The general idea here is to help banks use their first-party data to build personalized experiences by predicting user behavior.

Hyperplane was co-founded by Felipe Lamounier, Daniel Silva, Rohan Ramanath and Felipe Meneses, bringing together a team with extensive experience in the tech industry. Lamounier, who takes on the role of CEO, had spent the last seven years building a successful EdTech startup in Brazil called StartSe. Meanwhile, Daniel Silva and Ramanath had previously worked on large-scale AI systems at Google and LinkedIn, respectively.

The core hypothesis we started with was: what does it take to build a personalization layer for banks across the world?

Ramanath elaborates, “If you think of the big technology companies, they have a lot of first-party data, but they also have a lot of investments in data infrastructure and enterprise data warehouses to use all of this data to understand the consumer, to build personalization into every single product page, and finally build this into the consumer experience itself. The goal for Hyperplane is to provide a data intelligence layer that enables banks across the world to make use of their own first-party data.”

Lamounier also highlights the fact that banks possess highly detailed and specific data about their customers that is not available to other services.

One of the arguments that I use to sell to banks is that the data that these banks have about me as a client is much more vulnerable to catch my behaviors than what Google or Facebook have.

He adds, “It doesn’t matter if I go to the Porsche website – that doesn’t mean that I can buy a Porsche. But if I use Chase or Bank of America, they know the kind of restaurants I go to, which grocery store I frequent, and even how much I can afford when I order an Uber. All this data is within the bank’s own system.”

Currently, most banks offer very little by way of personalized experiences, setting the bar low. However, with heightened consumer expectations and a competitive banking market like Brazil, there is a growing demand for banks to provide a more personalized online experience. This is where Hyperplane comes in, offering APIs that enable banks to quickly and easily create personalization models. The team emphasizes that all deployments are private and that no data sharing takes place. They also utilize their own models for all their services.

At present, the company offers two modules – one for building audience segments and another for creating lookalike audiences that expand potential target audiences by identifying similar users.

We found that by building task-specific models, we can get a lot more mileage out of creating something custom and from the ground up.

Explains Ramanath.

Recently, Hyperplane launched Mandelbrot LLM, a model that specifically helps banks predict when a customer may churn or which users consider a given bank as their primary bank.

According to Hyperplane, one of their clients in Brazil, a neobank, saw a 46% increase in transaction volume for their credit limit division by using the company’s services. This was achieved by gaining a clearer understanding of their customers’ estimated income.

“Brazil has undergone a significant pro-competition movement in the last decade, and today, we see an ecosystem that embraces new technologies,” comments Lamounier. “The Hyperplane Cloud is easily scalable across markets, and we are excited to soon announce our first partnerships in the U.S.”

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Dylan Williams

Dylan Williams is a multimedia storyteller with a background in video production and graphic design. He has a knack for finding and sharing unique and visually striking stories from around the world.

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