MeltPlan Raises $14 Million in Seed Funding to Transform Construction Planning With AI

The construction industry has long been one of the most stubborn sectors when it comes to productivity and efficiency. Despite advances in project management tools, field management software, and building information modeling, the core problem has remained unsolved — construction projects routinely go over budget by nearly 30% and run beyond schedule by approximately 20%. These delays and cost overruns don't usually emerge from poor execution on-site; they stem from something far earlier in the process: the pre-construction planning phase. And a San Francisco-based startup named MeltPlan is now stepping in with a bold promise — to bring order, intelligence, and precision to that critical phase using purpose-built artificial intelligence. In a significant AI funding development, MeltPlan has announced that it has successfully closed a $14 million Seed funding round, backed by one of Silicon Valley's most respected venture capital firms, Bessemer Venture Partners, along with participation from noa and WND Ventures. This latest AI funding news confirms that investor confidence in construction technology powered by AI is stronger than ever, and MeltPlan is at the center of that momentum.

The Broken Planning Problem That Has Haunted Construction for Decades

Before understanding why MeltPlan's approach matters, it is important to grasp the depth of the problem it is solving. The construction industry, which is valued at roughly $14 trillion globally, has been facing a persistent productivity crisis. Projects regularly bleed money and time not because the workers aren't skilled or the materials are substandard, but because the decisions made during the early planning phase are made with incomplete, fragmented, and sometimes contradictory data. When teams are required to commit to scope, cost, schedule, and building codes before all the relevant data is assembled and cross-checked, the natural result is a cascade of change orders, last-minute redesigns, and costly rework that ripples through every subsequent stage of the project.

Existing software solutions have addressed different aspects of this problem, but none has tackled it holistically. Design tools like AutoCAD and Revit are excellent at handling aesthetics and helping teams visualize what a building will look like. Execution platforms manage on-site coordination and document control. Field management software keeps track of what's happening after the ground is broken. But the critical window between "here is our design idea" and "let us actually start building" — the preconstruction phase where trade-offs are analyzed, costs are locked in, and compliance is verified — has been largely untouched by technology. Teams still work through this phase manually, in silos, relying heavily on individual experience and institutional knowledge that often lives in someone's head rather than in a shared, interconnected system. MeltPlan was built specifically to fix this.

What MeltPlan Has Actually Built: The Planning Engine

At the heart of MeltPlan's platform is what the company calls its "Planning Engine" — an AI-native system that was designed specifically for the construction domain, not retrofitted from a generic large language model or an off-the-shelf AI platform. This is a distinction the company takes extremely seriously, and it's one of the reasons early adopters and investors have taken notice.

The Planning Engine is made up of four deeply integrated modules: code compliance, cost analysis, schedule optimization, and value engineering. These four modules work together simultaneously, which means that when a project team is evaluating a design decision, the system is simultaneously checking whether it meets building codes, calculating the cost implications, modeling the timeline impact, and identifying whether there's a more cost-effective or structurally efficient alternative. Traditionally, each of these assessments would be done by a different specialist, at a different time, with limited communication between them. MeltPlan collapses all of that into a single, unified workflow.

What makes this particularly impressive from a technical standpoint is the accuracy the system has already demonstrated. MeltPlan's AI models score above 95% on building inspector examinations — a benchmark that puts them ahead of most human practitioners. Compared to commercial retrieval-augmented generation (RAG) platforms that typically achieve around 85% accuracy, MeltPlan's proprietary models hit 93–98% accuracy on construction-specific tasks. These are not fine-tuned versions of existing consumer models; they are built from the ground up using construction-native training data, which gives them an understanding of construction methods, procurement constraints, and regulatory requirements that generic AI simply cannot replicate. The result is what the company calls "expert reasoning" — the system doesn't just surface information, it genuinely understands the context in which that information matters.

Equally important is the platform's commitment to transparency. In an industry where decisions have multi-million-dollar consequences and where accountability is legally and contractually defined, a "black box" AI system that produces recommendations without explanation would be almost entirely useless. MeltPlan takes the opposite approach, providing full visibility into how and why the system arrived at its conclusions, so project teams can audit, validate, and take ownership of every decision made through the platform.

The Leadership Team: Where Healthcare Disruption Meets Construction Expertise

Behind MeltPlan's technology is a founding team that brings together two seemingly different worlds — healthcare technology and construction management — in a combination that turns out to be highly complementary.

Kanav Hasija, the company's CEO, previously co-founded Innovaccer, a health technology company that grew into a $3 billion unicorn. His experience at Innovaccer was defined by one central challenge: building AI and data infrastructure that could make sense of extraordinarily complex, fragmented information ecosystems in an industry that is heavily regulated, deeply risk-averse, and where errors carry serious consequences. Sound familiar? The parallels between healthcare and construction are striking. Both industries are data-rich but insight-poor, both are governed by dense regulatory frameworks, and both have historically resisted digital transformation even while suffering from obvious inefficiencies. Hasija's instinct to apply healthcare's AI transformation playbook to construction is not just a clever pivot — it is a structurally well-reasoned bet, backed by real experience navigating those same dynamics in a different vertical.

His co-founder, Tanmaya Kala, who serves as COO, brings the other half of the equation. With extensive hands-on experience as a project executive at DPR Construction — one of the most respected general contractors in the United States — Kala has personally managed multimillion-dollar commercial, healthcare, and life sciences construction projects. That means he has lived the problem that MeltPlan is solving. He understands which decisions are being made too late, which trade-offs get missed, and where the manual workflows break down under pressure. The combination of Hasija's AI systems expertise and Kala's deep industry domain knowledge creates a founding team that is credible both with investors and with the construction professionals they are trying to serve.

Together, they have articulated a vision that is deliberately understated but deeply ambitious: make construction "boring." What they mean by this is that the goal is not to glamorize or dramatize the building process, but to make it so well-planned, so thoroughly analyzed in advance, and so systematically de-risked that the actual execution phase becomes predictable and routine. In an industry where chaos and crisis are practically built into the process, "boring" would be a revolutionary achievement.

Bessemer-Led $14M Seed Round: What the AI Funding Signals for ConTech

This AI funding round is a significant signal for the construction technology sector as a whole. Bessemer Venture Partners is not a firm that bets on incremental improvements. Its investment portfolio includes companies like LinkedIn, Twitch, Shopify, and Pinterest — all platforms that fundamentally restructured the industries they entered. When Bessemer leads a $14 million seed round for a company that has only existed since 2025, it is a strong endorsement of both the founding team and the market thesis.

The AI funding news around MeltPlan comes at a time when investors across the board are becoming more discerning about where they deploy capital in the AI space. The initial wave of AI investment was characterized by enthusiasm for large language models and general-purpose AI tools. What is emerging now is a more mature second wave focused on vertical AI — purpose-built systems that solve specific, high-stakes problems in industries like construction, healthcare, legal, and logistics. MeltPlan fits squarely in this category, and the Bessemer-led round validates the idea that purpose-built, domain-specific AI can command premium valuations even at the seed stage.

The participation of noa and WND Ventures alongside Bessemer adds further depth to the round. Investors from noa have noted publicly that MeltPlan's technical moat comes not just from its models but from the product architecture and the depth of construction domain expertise baked into every layer of the system. The combination of high accuracy, expert reasoning, and full transparency gives MeltPlan a competitive advantage that would be extremely difficult for a general-purpose AI platform to replicate, and equally difficult for a traditional ConTech company to match without rebuilding its AI foundation from scratch.

Early Pilots, Competitive Landscape, and the Road Ahead

MeltPlan is already putting its platform to work in the real world. The company is currently running pilots with DPR Construction in California and Innovo Group in the United Arab Emirates — two very different market contexts that together demonstrate the platform's adaptability across building types, regulatory environments, and geographies. DPR Construction is one of the top 50 general contractors in the United States, known for technically complex projects in healthcare, life sciences, and advanced technology facilities. Innovo Group operates in one of the world's fastest-growing construction markets. These are not vanity pilots; they are partnerships with organizations that have sophisticated requirements and extremely low tolerance for tools that don't deliver measurable results.

The competitive landscape is worth examining. Autodesk Construction Cloud dominates the execution phase. Procore is the established leader in field management and project coordination. Reconstruct focuses on building information modeling and visual site tracking. What is striking about this landscape is that none of these platforms are focused on the preconstruction decision-making phase in the way MeltPlan is. They all assume that the early planning has already been done and the project is moving into execution. MeltPlan is operating in the white space before execution begins — and by the time these other platforms enter the picture, the most consequential decisions have already been made. If MeltPlan can establish itself as the definitive platform for preconstruction intelligence, it sits at the very top of the construction technology stack, upstream from every other tool in the ecosystem.

The $14 million in seed funding will be directed toward accelerating the development of MeltPlan's connected decision systems and bringing the first three product verticals of the platform to market. The exact details of these verticals have not yet been disclosed, but early indications suggest they will map closely to the four modules of the Planning Engine: code compliance, cost analysis, schedule optimization, and value engineering. Given the pace at which the team has moved since the company's founding in 2025 — building proprietary AI models with near-human accuracy, securing partnerships with major industry players, and closing a significant institutional seed round — the timeline to those launches appears aggressive and credible at the same time.

The broader vision that MeltPlan is working toward is nothing less than a complete reimagination of how the construction industry allocates its intellectual resources. Today, the most intense scrutiny and the most experienced minds are deployed during construction, when changes are expensive and mistakes are visible. MeltPlan wants to flip that model entirely, making preconstruction the phase that demands the most rigor, the most analytical depth, and the most informed decision-making — and then letting everything that follows flow from a foundation that was built right the first time. In an industry that the global economy absolutely depends on, closing that productivity gap is not just a business opportunity. It is a genuinely important problem to solve, and AI funding news like this round signals that the world is finally paying attention.