MeltPlan
MeltPlan develops an AI-native planning engine for the construction industry that integrates building code compliance, quantity takeoffs, bid leveling, scheduling, and value engineering into a single pre-construction workflow. Founded in 2025 and headquartered in Berkeley, California, the company targets the point where most project risk and cost overruns originate.
- Founded: 2025
- HQ: Berkeley, CA
- Funding Round: Seed (2026)
- Total Raised: ~$14M
- Team Size: ~30 (as of May 2026)
- Sector: Construction Technology / Vertical AI (Preconstruction)
Core Data Grid
| Funding Round | Lead Investors / Notable Backers | Total Raised (approx.) | HQ Location | Industry Sector | Estimated Team Size | Key Partners / Validation |
|---|---|---|---|---|---|---|
| Seed (2026) | Bessemer Venture Partners (lead), noa, WND Ventures | $14M | Berkeley, CA | Construction Technology / Vertical AI | ~30 | DPR Construction (pilot & advisor ties), Innovo Group (UAE); >95% accuracy on building inspector-level code tasks |
MeltPlan Leadership & Structural Breakdown
Key Leadership
- Kanav Hasija, CEO & Co-founder — Previously co-founded and scaled Innovaccer, a healthcare data and AI platform, to a $3B+ valuation. Brings systems-thinking and complex-industry data platform experience.
- Tanmaya Kala, PE, COO & Co-founder — Former Project Executive at DPR Construction (one of the largest U.S. general contractors). Stanford civil engineer with 17+ years managing large commercial, healthcare, and life sciences projects.
- Prithviraj Damodaran, CTO — AI researcher and builder with prior systems work at GE, Motorola, Bank of America, and Trimble. 100+ citations at top conferences (NeurIPS, ACL, CVF); expertise in search/ranking and open-weight model training.
Primary Competitors
- Procore
- ALICE Technologies
- Togal.AI (or Autodesk Construction Cloud for broader AEC comparison)
Core Use Cases & Market Problem
- General contractors and estimators facing slow, manual, error-prone takeoffs and frequent scope gaps during bidding.
- Architects, engineers, and inspectors needing rapid, traceable, project-specific building code research instead of fragmented manual searches.
- Owner and project teams dealing with siloed preconstruction data that leads to late changes, rework, and margin erosion once construction begins.
Plain English Explanation
MeltPlan functions as a construction-native decision layer. It ingests plans and documents, applies domain-specific models to extract quantities, check code compliance with citations and reasoning, level subcontractor bids, and model schedule/value scenarios — all while exposing its logic so human experts can audit and act.
Target Customers & Adoption Context
Primary buyers and users are general contractors, specialty trades, architects, engineers, developers/owners, and building departments. The platform removes the core friction of preconstruction: manual extraction from drawings and PDFs, inconsistent code interpretation, and lack of connected scenario modeling. Early adopters are forward-leaning enterprise contractors who already invest heavily in preconstruction to reduce downstream change orders.
Capital & Traction Signals
Raised $10M Seed in February 2026 (total ~$14M) led by Bessemer Venture Partners with participation from noa and WND Ventures. Commercial traction includes active pilots and work with DPR Construction (California) and Innovo Group (UAE). AI models have achieved >95% accuracy on building inspector examinations. The platform comprises four integrated systems (Code, Cost/Takeoff/Bid, Schedule, Value), with initial modules launching or recently launched. Investor commentary highlights rapid data connectivity and conversational project interaction in early deployments.
Editorial Assessment (Investor Lens)
MeltPlan sits at a high-conviction intersection in the 2026 cycle: vertical AI applied to one of the largest, most document-intensive, and chronically under-digitized industries. Preconstruction remains the highest-leverage point for reducing the industry’s well-documented productivity and overrun problems. Validation is strong — Bessemer’s enterprise software track record plus noa’s participation, combined with a founder who previously scaled a regulated-industry data platform to unicorn status and a co-founder with direct general contractor operating experience at DPR. The technical bench (CTO research pedigree) supports construction-native model development with built-in traceability, a material differentiator versus generic LLM overlays. Momentum is visible in marquee contractor pilots and benchmark performance. Watchpoints include sales cycle length in a relationship-driven sector and the speed at which incumbents (Procore, Autodesk) integrate comparable AI features. Public signals point to credible potential for MeltPlan to become the connected system of record for pre-construction decisioning, with defensibility likely to come from workflow embedding and proprietary construction data loops rather than raw model performance alone.
Last Updated: June 2026
Sources
- https://www.meltplan.com/ and https://www.meltplan.com/blogs/we-raised-14-million-to-build-the-planning-engine-for-construction
- https://www.bvp.com/news/optimizing-pre-construction-workflows-and-planning-with-meltplan
- https://www.noavc.com/stories/why-we-invested-in-meltplan
- https://www.thesaasnews.com/news/meltplan-raises-10-million-seed-round/
- https://www.finsmes.com/2026/03/meltplan-raises-10m-in-seed-funding.html
- Tracxn and LinkedIn company/founder profiles (team size, background verification)
