Cascade secures $3.5 million to identify construction projects prior to the existence of bids.

      In recent months, a bond was filed, a parcel of land changed ownership, and the winner of a nine-figure construction project was discreetly determined. No request for proposals was issued, and most firms that could have pursued the opportunity were unaware of its existence. This interval, which exists between when a project begins to show signs and when it goes public for bidding, is the premise behind Cascade, an AI platform designed for architecture, engineering, and construction firms.

      This week, the company announced it had secured $3.5 million from Andreessen Horowitz's Speedrun program, as well as from Ada Ventures, Blitzscaling Ventures, Indico Capital, shuckerVC, G2C Ventures, and Snowball VC.

      The core idea is that substantial building projects generate paperwork well before tenders are released. A bond filing indicates a project is taking form, while a property sale signals a developer taking action. A mention in a county capital plan refers to a structure that has yet to be built, and which someone will eventually secure.

      Cascade claims to continuously monitor these indicators, drawing data from permits, capital plans, property transactions, earnings calls, budget announcements, and meeting minutes, and aims to link them to where opportunities are emerging, the nature of those opportunities, and which firms are in a favorable position to secure them.

      When it identifies a prospect, the platform evaluates each opportunity for suitability and seeks warm introductions through existing relationships within a firm's Outlook and other software.

      The founders liken their approach to finance, with Joana Ferreira, Cascade's co-founder and chief technology officer, stating, “Hedge funds analyze vast amounts of data to forecast stock movements. We apply that same logic to anticipate construction projects.”

      The initial clientele leans towards high-profile projects. According to Cascade, its clients have worked on notable developments such as JFK and LaGuardia airports, data centers, nuclear facilities, and luxury hotels, with a collective total of over $10 billion in project opportunities surfaced through the platform, a figure the company has not detailed further.

      Tim Johannesson, a principal at the luxury architecture firm Smallwood, noted that Cascade enabled his firm to discover and win a $6 million project that he wouldn't have otherwise noticed. He remarked, “I’ve been in the industry for 30 years. A project commenced just a few blocks from me, and I wasn’t even aware it was out for bid.”

      Cascade was co-founded by Hannia Zia and Ferreira, both former Google employees who met at UnlikelyAI, a startup founded by William Tunstall-Pedoe, the British engineer known for creating Amazon’s Alexa. Zia served as the vice president of product there, while Ferreira headed the AI platform.

      Their entry into the construction sector is rooted in personal experience: Ferreira grew up in a Portuguese town built on construction and carpentry, and Zia's father attempted and failed to establish a construction business.

      Their first customer, Munoz Engineering, which has worked on projects including LaGuardia, Moynihan Train Hall, and the Cuomo Bridge, emerged from discussions Zia had with CFOs in New York. "Cascade assists us in planning strategically in the highly competitive AEC industry in NYC," said Syed Irfan Raza, the firm’s CFO.

      Cascade's broader strategy relies on networking. Even a single house involves about twenty companies, and larger projects involve even more, so the argument is that as more firms join, the platform can better match them with one another for partnerships, subcontracting, and collaboration across regions.

      Whether this will yield the desired results as envisioned by the founders will likely take more than just a few months of new signings to establish. For now, the proposition is more straightforward and easier to validate: discover the work before the competition is aware of it.