For decades, infrastructure professionals have struggled to find useful information on prior transactions. The agreements contain vital information—on terms, conditions, and pricing. Without such information, each project has to be structured and developed from scratch.

Every single time.

It can take years to develop a single project. This is costly. This is exhausting.

As infrastructure professionals, we know this first-hand. Before we started Infraclear, our team collectively spent 47 years trying to develop projects in 22 countries around the world.

Every developer, lender, institutional investor, lawyer, and government official would tell us, “If only we had standardized data, we could…

"Develop projects faster"
"Bring more bankable projects to market"
"Make procurement simple and transparent"
"Understand the risks in our messy portfolios"
"Make infrastructure a liquid asset class"

And maybe…just maybe, develop sustainable projects fast enough to help us find a way out of the climate crisis.

Yet, no one seemed to have this data.

We were tired of all this talk. The climate crisis is upon us. The energy crisis is upon us. If we kept doing the things the way we have done in the past, nothing would change.

We decided to do something about it.

We took a risk. We quit our jobs. We went out on a limb, and bet that we could obtain the data. And we knew that modern natural language processing and machine learning tools could analyze some of the messiest data around.

We’re doing it.

Today, we’ve already built one of the world’s largest infrastructure data platforms. We have collected thousands of project and financing agreements from around the world.

Using machine learning tools, we are making this data easy to use. And we’re putting it at your fingertips.

We’re building this for you. The developers, lenders, investors, construction companies, government officials, lawyers, and NGOs who work so hard to develop and finance the infrastructure that the world needs.

Our platform is built to help you make decisions with facts. To make decisions faster. To simplify your life. To help you conduct analysis you dreamed of. And to help you solve our climate crisis.