SOM Alum Raises $6 Million for AI Construction Startup

In a significant boost for the construction technology sector, Ziv Levi, a 2026 graduate of the Yale School of Management (SOM), has announced that his startup LeanCon has secured $6 million in seed funding. This round exceeds the company’s initial $3 million goal, signaling strong investor confidence in LeanCon’s innovative approach to tackling longstanding inefficiencies in the construction industry.

LeanCon’s Breakthrough: Cutting Pre-Construction Planning from Months to Minutes

At the heart of LeanCon’s offering is a platform that redefines pre-construction planning, one of the most labor-intensive and costly stages in any building project. Traditionally, this phase involves teams poring over designs, budgets, timelines, and logistics, often taking several months and costing upwards of $2 million per project. Delays here can cascade into overruns, missed opportunities, and lost bids in a highly competitive market.

LeanCon changes that equation dramatically. The company’s AI-powered technology generates detailed projections in just about seven minutes, all at near-zero cost. This isn’t just about speed—it’s about precision and scalability. General contractors and developers using LeanCon can now evaluate and plan 100 times more projects annually, achieving 90% accuracy in estimates while shortening overall schedules by 20%. The result? They win more bids, optimize resources, and deliver projects more efficiently.

“This milestone directly accelerates LeanCon’s mission because it enables us to finalize the development of our core technology and scale it into a product that will create a significant impact on the industry, fundamentally transforming the way construction projects are analyzed, bid, and planned,” said Levi.

This rapid turnaround addresses a core pain point in construction: the sheer volume of opportunities that teams must sift through. Pre-construction teams often review hundreds of potential projects, but only about 8% advance due to fierce competition and resource constraints. LeanCon’s platform automates key elements like scope definition, cost estimation, logistics planning, construction sequencing, and scheduling, freeing human experts to focus on high-value decisions.

The Funding Round: Backing from Industry Heavyweights

The $6 million seed round was led by Ibex Investors, with additional participation from Fusion VC, Newman Architects, TCA LA, Connecticut Innovations, and Siegel Capital. What stands out is the involvement of prominent angel investors with deep roots in construction, real estate, and technology. Among them is Phil Bernstein, who previously served as Vice President of Architecture, Engineering, and Construction (AEC) at Autodesk and now holds the position of Deputy Dean at the Yale School of Architecture.

This lineup of backers isn’t coincidental. Investors drawn to LeanCon recognize the untapped potential in AI for construction. The construction industry, valued at trillions globally, has been slower than others to adopt digital tools, relying heavily on manual processes and gut instinct. LeanCon’s focus on the pre-construction phase—often overlooked in favor of flashy on-site tech—positions it as a smart bet for disruption.

For context, seed funding in construction tech has been on the rise, with startups leveraging AI to streamline everything from design to supply chain management. LeanCon’s oversubscribed round reflects a broader trend: venture capital flowing into solutions that promise measurable ROI through efficiency gains. Doubling the target amount suggests that early traction and the team’s expertise convinced investors that LeanCon could capture a meaningful slice of this market.

Founders’ Journey: From Construction Sites to AI Innovation

Ziv Levi and his co-founder Sapir Tubul bring authentic, hands-on experience to LeanCon. Both grew up around bustling construction sites, gaining an early appreciation for the industry’s complexities. Later, they worked as engineers on large-scale projects, witnessing firsthand how pre-construction bottlenecks derail progress.

Imagine a team racing against deadlines, juggling blueprints, supplier quotes, and regulatory hurdles—only to realize midway that a cost estimate is off by millions. Levi and Tubul saw this repeatedly: despite evaluating hundreds of opportunities, just 8% of projects moved forward. The rest? Shelved due to inaccurate planning or prohibitive upfront costs.

This insight drove them to build LeanCon as the world’s first AI-powered pre-construction engineering team. Their platform doesn’t just crunch numbers; it applies unique logic derived from proprietary data and lessons from past projects. This ensures every output is customized—secure, tailored to the client’s business, and revealing efficiencies they might not have considered.

In the broader landscape of AI construction startups, LeanCon stands out by emphasizing data privacy and uniqueness. Unlike generic tools, it doesn’t recycle one-size-fits-all models. Instead, it integrates designs, market data, and past project benchmarks to produce comprehensive reports that guide decisions with confidence.

How LeanCon’s Technology Works: A Deep Dive

To understand LeanCon’s value, it’s helpful to break down the traditional pre-construction process and how AI intervenes.

Traditional Challenges in Pre-Construction

• Time-Intensive Analysis: Teams manually review architectural plans, soil reports, and zoning laws, often spanning 3-6 months.
• High Costs: Involving architects, engineers, and consultants can exceed $2 million for complex projects.
• Low Throughput: With only 8% of bids advancing, firms miss out on revenue from viable opportunities.
• Error-Prone Estimates: Human oversight leads to inaccuracies, resulting in 20-30% overruns on average.

The construction sector’s fragmented nature exacerbates these issues. Suppliers vary by region, labor costs fluctuate, and external factors like weather or material shortages add unpredictability.

LeanCon’s AI-Driven Solution

LeanCon’s platform acts as a virtual engineering team, automating the grunt work while enhancing human judgment. Here’s how it operates:

1. Input Integration: Users upload designs (e.g., BIM files or 2D plans), site data, and project parameters. The AI parses this instantly, cross-referencing with real-time market data like material prices and labor rates.

2. Automated Scope and Costing: Using proprietary algorithms, the system defines project scope—identifying required trades, quantities, and sequences. Cost estimates factor in historical benchmarks, adjusted for current conditions, achieving 90% accuracy.

3. Logistics and Scheduling: AI simulates construction flows, optimizing crane placements, material deliveries, and crew assignments to shave 20% off timelines.

4. Scenario Modeling: Beyond basics, the platform generates multiple “what-if” scenarios, surfacing hidden efficiencies like alternative sequencing or supplier swaps that could save costs.

5. Output Delivery: In seven minutes, users receive a detailed report with visuals, risk assessments, and actionable insights—all exportable for bids or stakeholder presentations.

What makes this powerful is the proprietary data layer. LeanCon aggregates anonymized insights from past projects, building a knowledge base that evolves with each use. Security is paramount: client data remains isolated, ensuring compliance with industry standards.

Aspect	Traditional Method	LeanCon AI Platform
Time Required	3-6 months	~7 minutes
Cost per Project	Up to $2 million	Near-zero
Annual Project Capacity	Limited (e.g., 10-20 evaluations)	100x more
Accuracy	Variable (70-80%)	90%
Schedule Impact	Potential overruns	20% shorter

This table highlights the transformative potential, making abstract benefits concrete for decision-makers.

In practice, the platform’s adaptability shines. For a high-rise in New York, it might prioritize vertical logistics; for a suburban development, horizontal phasing. By turning chaos into structure, LeanCon converts pre-construction from a cost center into a high-margin engine.

Real-World Impact: Deployments and Broader Implications

LeanCon isn’t just theoretical—it’s already making waves. The platform is deployed across more than $650 million in active development projects in New York, partnering closely with one of the country’s largest privately held construction and real estate development firms.

This collaboration underscores LeanCon’s immediate value. Early users report faster bid wins and reduced planning errors, allowing them to scale operations. Beyond private sector gains, the technology is adapting for public-sector planning. In government projects, where budget overruns plague taxpayers (often exceeding 50% of initial estimates), LeanCon’s precision could save millions.

Economically, the ripple effects are substantial. By boosting profitability, LeanCon enables firms to hire more workers, invest in training, and take on additional projects. This supports job growth in an industry that employs over 7 million in the U.S. alone. On a macro level, efficient construction means faster infrastructure delivery—think bridges, schools, and housing that meet growing demands without ballooning costs.

Consider the environmental angle, too. Shorter planning cycles mean less time wasted on dead-end bids, reducing paper trails and energy use in initial assessments. As sustainability becomes a priority, LeanCon’s data-driven optimizations can minimize material waste and carbon footprints from the outset.

Why Investors Are Betting Big on Pre-Construction AI

Investors flocked to LeanCon because it targets the pre-construction phase—the quiet powerhouse of project success. As Levi puts it:

“Our core operating belief is that construction begins long before the first shovel hits the ground. It begins with the initial decisions that quietly lock in a project’s fate, determining its final cost, timeline, and risk profile. Our investors immediately recognized that this phase, which has traditionally been analog, chaotic, and reliant on intuition, represents the last truly untouched frontier ripe for massive disruption.”

This phase accounts for up to 30% of total project costs but has seen little innovation compared to on-site tools like drones or BIM software. LeanCon fills that gap, offering a scalable, AI-centric solution that integrates seamlessly with existing workflows.

The construction tech space is heating up, with AI applications spanning predictive maintenance to robotic building. Yet, pre-construction remains underserved. LeanCon’s edge lies in its founders’ domain expertise and the platform’s proven accuracy, making it a low-risk, high-reward investment.

Looking Ahead: Growth Plans and Company Culture

With fresh capital in hand, LeanCon is poised for acceleration. Over the next 12 to 18 months, the focus will be on:

• Achieving Product-Market Fit: Refining the platform based on user feedback to ensure seamless adoption across firm sizes.
• Strategic Expansion: Scaling beyond New York to other major markets like California and Texas, where construction booms.
• Building Sustainable Growth: Investing in R&D for advanced features, such as real-time collaboration tools or integration with emerging tech like digital twins.
• Cultivating Company Culture: Prioritizing a collaborative environment that attracts top talent in AI, engineering, and construction.

Levi emphasizes that LeanCon isn’t tweaking old methods—it’s creating a new paradigm.

“We aren’t simply improving an old process. We are building the intelligent operating layer that delivers automated, structured planning and AI-driven cost, time and risk insights. This capability immediately converts what was a point of chaos into a predictable, high-margin engine for general contractors and developers.”

As the startup grows, challenges remain: navigating data regulations, competing with incumbents, and educating a conservative industry on AI’s benefits. But with strong backing and real deployments, LeanCon is well-equipped to lead the charge.

The Bigger Picture: AI’s Role in Modernizing Construction

The construction industry faces headwinds—labor shortages, rising material costs, and supply chain disruptions. AI tools like LeanCon’s are part of a necessary evolution, helping firms stay competitive in a digital-first world.

For developers, the appeal is clear: more bids won, fewer surprises, and higher margins. For the ecosystem, it means safer, timelier projects that benefit communities. As LeanCon scales, it could set a benchmark for how AI construction startups integrate intelligence into every phase, starting from the planning desk.

Ziv Levi’s journey from SOM alum to funding success story highlights the power of blending business acumen with technical insight. LeanCon’s $6 million raise isn’t just a win for the company—it’s a vote of confidence in smarter, faster construction for all.