Merlin AISummer 2024Active☆Watch⊞Compare

Merlin AI is one of 2067 AI / ML companies tracked from Los Angeles, CA, USA, on record since 2024. By capital raised it ranks mid-pack (ahead of 62% of sector peers), and mid-pack by modeled valuation est..

Ranking is computed against this company's own sector cohort — reported capital is fact; valuation tiers are modeled.

AI analyst read est. — model-extracted from this company's public description, not a verified fact. 30%

operates a technology-led product inferred from public copy

Grounded in: “You are a venture analyst”

AI powered ERP for Construction

Merlin is an AI-powered ERP for construction companies. We provide construction companies with a single, AI-powered platform to manage their entire business operations. Our platform unifies project management, materials management, finance, estimating, and CRM—traditionally scattered across multiple systems—into one cohesive solution. For the first time, construction firms can automate and oversee every aspect of their projects in a single, intuitive system. Today, construction companies pay for 8-17 different tools - that we eliminate the need for. We reduce - Manual work by 60% - Cut software costs by $10,000 monthly - Complete projects 3x faster. Why Now? We're witnessing a perfect storm of factors: decades of stagnation in traditional ERP systems, a multi-billion-dollar industry built on misaligned incentives, and the transformative potential of AI. This confluence creates a rare cyclical opportunity for market upheaval. The last major shift in this space occurred in the 1990s with the advent of digital systems, and now, 30 years later, we're on the cusp of another seismic change. Customers are crying out for innovation and as AI reshapes the landscape, early customer signals indicate an eagerness for smarter, more efficient systems. It's a unique window of opportunity that opens perhaps once in a multi-decade chance to redefine an entire industry's operational backbone. Team: KS, a BITS Pilani grad and successful startup co-founder, and Ayantika, an IIT alumni and tech expert, bring extensive coding and product development expertise together bringing about over a decade of technical expertise. Sneha ( that’s me), with over a decade of experience in supply chain management and lean manufacturing within the construction industry, has lived the pain of using ERPs in this industry.

As reported in public records reported — not modeled.

Solid bars are reported offering amounts reported; hatched bars are the modeled post-money valuation est. — both on one shared scale so you can read raise-vs-worth at each round directly. Use the toggles to overlay data labels and the niche-peer / market average value lines.

No round amounts on record to chart.

No staged rounds to sequence.

Round size and date are reported; the stage label is inferred from round size. Valuation is modeled from stage benchmarks. Directional, not a quoted figure.

Not enough modeled valuation points to chart a trajectory.

Benchmarked against 2067 companies in AI / ML. Each bar is a median (the middle company, not an average — outliers don't skew it). Two yardsticks: real money raised (reported on Form D) and modeled value (our estimate est.). These are whole-sector medians across all stages, except the per-stage row.

Raised more than 62% of sector peers (real $). Modeled value above 62% of peers (estimate).

Stage is inferred from round size est., not reported on the filing — a round's dollar size maps to a bucket: Pre-Seed <$1.0M · Seed $1.0M–$4.0M · Series A $4.0M–$15M · Series B $15M–$40M · Series C $40M–$100M · Series D+ $100M–$400M · Growth/Late >$400M.

Predictive signals are modeled est. from this company's own cadence and step-up, plus sector benchmarks — directional, not advice. Peer set and a CSV export live in your analyst workspace.

Merlin AI is an official record sourced from the U.S. Securities and Exchange Commission (SEC). U.S. data is aggregated from SEC Form D filings.

Nearest neighbours across the whole database — matched on sector, stage and capital scale, and on shared operators (officers or directors named at both companies in public filings). A discovery shortlist, not a valuation cohort — verify before acting, the same way modeled figures are directional.

Matched by meaning, not labels — a local language model reads each company's name, sector and description and ranks the closest in that learned space. This catches look-alikes that cross sector boundaries; the structured list above explains its matches, this one trusts the text. Directional, like every modeled signal here.

See where Merlin AI sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.

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