The problem isn't lack of data.
It's the workflow in between.

We built Kamba to remove the workflow drag around financial data.

In financial services, the problem is rarely lack of data. It is the work between having data and being able to trust and use it. Teams still spend too much time on the steps that come before the analysis:

Searching Validating Backtesting Negotiating Provisioning Integrating Monitoring

Kamba turns that manual workflow into a governed system that produces finished, auditable analysis. Kamba Analyst compresses the path from question to trusted data to finished output — discovering the right datasets, validating quality and lineage, testing relevance, and producing decision-ready artifacts inside the operating environment your firm already requires.

We are building the system that lets financial professionals spend their time on judgment — not on the workflow reconstruction that currently precedes it.

Our thesis

What we believe

Financial professionals should spend time on judgment, not workflow reconstruction.

We spent years at Bloomberg, IHS Markit, and the firms they served watching analysts spend the majority of their time on data preparation rather than the analysis itself. That ratio is wrong and fixable.

What we build

Systems built for the most demanding buyers in finance — where governance isn't optional.

Kamba is not a general AI tool adapted for finance. It is built from the ground up for regulated environments where auditability, lineage, and compliance are requirements, not features. The bar we build to is an IC, a compliance review, or a client meeting — months later.

Why now

Data volumes keep growing. AI access is expanding. But the workflow between the two is still broken.

Alt-data budgets are expanding across the buy-side. Internal AI usage has roughly doubled year over year. The firms that win will treat data and AI as a single operating system — not two separate projects with a manual process in between.

From the founder

"The data existed. The analysts were capable. The problem was always the time between the question and the moment the data was trusted enough to use."

I spent over a decade at Bloomberg, IHS Markit, and Demyst watching how the best investment teams in the world interacted with financial data. The constraint was never intelligence or access. It was the manual workflow between a question and a finished, defensible output. Kamba is the system I wish had existed throughout that time.

Sebastean Leoni · Co-Founder & CEO, Kamba Group

Leadership

Our leadership team

Operators, technologists, and industry leaders with deep experience across trading, data, and financial infrastructure.

Co-Founder

Sebastean Leoni

Co-Founder & CEO

Co-Founder

Ignacio Berdinas

Co-Founder & CTO

Investor / Advisor

Sebastian Gunningham

Investor / Advisor

Jean-Louis Lelogeais

Investor / Advisor

Marco Viola

Investor / Advisor

Nicolas (Gucho) Aguzin

Investor / Advisor

Our DNA

Built inside the problem.

This team built and sold data infrastructure at the firms that defined the institutional data problem. Bloomberg. IHS Markit. Amazon. JPMorgan. Bank of America. The workflow gap Kamba is closing is one we watched from the inside.