27 Jul 2026 3 min read Western Hemisphere

Cascade Raises $3.5M to Help Construction Firms Find and Win Projects Before They're Public

Cascade CEO Hannia Zia and CTO Joana Ferreira

Cascade, a New York-based startup founded in 2025 by CEO Hannia Zia and CTO Joana Ferreira, announced on July 22 that it raised US$3.5 million in a seed round led by Andreessen Horowitz's Speedrun program. Ada Ventures, Snowball VC, Blitzscaling Ventures, Indico Capital Partners, shuckerVC, and G2C Ventures also participated. Zia and Ferreira are both former Google engineers who previously worked together at UnlikelyAI, where Zia served as VP of Product and Ferreira led the AI platform team.

Cascade's software uses AI to predict construction projects before they reach the public bidding stage, monitoring signals such as bond filings, building permits, capital plans, property transactions, earnings transcripts, budget announcements, and government meeting minutes to flag opportunities and match them to architecture, engineering, and construction (AEC) firms based on their capabilities. Customers, including luxury architecture firm Smallwood, Florida-based general contractor S.A. Casey Construction, and engineering firm Munoz Engineering, have used the platform to identify more than US$10 billion in project opportunities, spanning airports, data centers, hotels, and nuclear facilities; Smallwood recently won a US$6 million project sourced through Cascade. The company plans to use the new funding to expand go-to-market efforts, attend industry events, and hire engineers.

Market Context

Cascade is entering a $900 billion global construction industry where project discovery has historically been manual, fragmented, and relationship-driven, with firms often learning about opportunities only after formal requests for proposals are issued. The company positions itself against established players like GovWin IQ and ConstructConnect, arguing that its predictive, AI-native approach surfaces opportunities earlier in the pipeline and pairs that intelligence with proposal-writing and bid support, rather than functioning purely as a project database.

The round reflects a broader wave of venture interest in AI tools built for traditionally offline, paperwork-heavy industries such as construction, where incumbents' data has often lagged behind newer, machine-learning-driven approaches to forecasting demand. Cascade's backing from a16z's Speedrun accelerator, known for funding gaming and consumer-adjacent technical founders as well as vertical AI startups, adds visibility to a company betting that predictive lead generation can become a standard layer of enterprise software for the AEC sector.

The Signal

"Every time a customer wins a bid, they give feedback, so the system keeps getting smarter." — Joana Ferreira, co-founder and CTO, Cascade

Regional Relevance

For the United States: Cascade's platform draws on federal, state, and local project data across the country, meaning its predictive accuracy and usefulness scale directly with the pace of US infrastructure and commercial construction spending. As federal and state governments continue funneling money into airports, data centers, and public infrastructure, tools that help firms identify and win that work earlier could shape which companies capture a disproportionate share of contract awards, with downstream effects on regional job creation and project timelines.

For New York City's tech and construction ecosystem: Founded and headquartered in New York, Cascade adds to the city's growing cluster of vertical AI startups targeting traditionally analog industries. Its early customer base, including firms tied to major New York infrastructure projects like LaGuardia Airport and Moynihan Train Hall, underscores the city's dual role as both a testing ground for the platform and a hub of the large-scale construction activity the company is built to track.

The Other Side

Can Cascade's predictive data really outperform incumbents with decades of relationships and records? GovWin IQ and ConstructConnect have long-established data pipelines and customer bases; Cascade's edge rests on being "AI-native" and predictive, but it remains an open question whether that translates into materially better win rates or simply repackages information sophisticated firms already track through their own networks.

Is $3.5 million enough to compete in a market with slow, relationship-driven sales cycles? Construction firms are known for cautious, long procurement processes, and building trust with enterprise AEC customers typically takes years; a seed-stage budget may constrain how quickly Cascade can build the sales and customer-success capacity such cycles demand.

Does automating early-stage opportunity discovery risk commoditizing business development relationships that have long differentiated firms? If every subscribing firm receives the same predictive signals about upcoming projects, the competitive advantage may shift away from who has the best relationships and toward who can act on Cascade's alerts fastest, a dynamic that could reshape, rather than simply streamline, how contracts get won.