Trebellar, an AI native corporate real estate management platform, has raised $18 million in Series A funding led by Blossom Capital to scale its engineering and go to market teams while enhancing its AI capabilities.
Trebellar’s $18M Series A positions the San Francisco-based company as a vertical AI platform for corporate real estate (CRE), one of the last major enterprise functions still heavily reliant on spreadsheets, disconnected tools, and external consultants. The round was led by Blossom Capital (A dedicated Series A firm with ~$1.5B AUM, known for high conviction bets and portfolio companies including Checkout, Moonpay, Pigment, and Tines). Participation came from existing backers Haystack and Alt Capital, plus 1Flourish and Bynd Venture Capital.
This follows a $3.5M seed round in July 2023 from Haystack, Alt Capital, KFund, and Jetstream. Total capital raised is now approximately $21.5M. Proceeds will fund growth of engineering and go to market teams, deeper AI capabilities, and broader enterprise customer acquisition.
What is Trebellar?
Trebellar was co-founded by Diego Ferreiro Val (CEO; former VP of Engineering at Salesforce, early engineer there with infrastructure and data ingestion expertise) and David Garcia Quintas (CTO; AI/infrastructure background from Google, Waymo, and CERN). Both are Spanish; the company name derives from a Galician word meaning “to play with something with the intent of mastery.” The idea originated as a pandemic era home automation side project that pivoted after interest from Salesforce’s workplace technology team, which faced the same data fragmentation problems at enterprise scale.
Leadership includes Adam Sewall as CRO/COO. The company recently added Dave Radcliffe as an advisor; he previously led Google’s real estate expansion under Eric Schmidt, Larry Page, and Sundar Pichai. Team experience spans Salesforce, Google, Waymo, and Verkada, combined with CRE domain knowledge.
What is Trebellar’s technology?
Trebellar builds an AI native system of record and decision layer for CRE teams (workplace, facilities, real estate). Core problem it addresses: leases, space, headcount, utilization, occupancy (badges/WiFi/sensors), costs, HR data, surveys, and market information live in silos (spreadsheets, PDFs, disconnected software). Decisions therefore require weeks of manual reassembly; traditional dashboards show the past, and consultant reports arrive outdated.
The platform unifies data via a CRE-specific ontology that normalizes and connects sources (APIs, CSVs, internal documents). Purpose built AI agents then plan, analyze, and execute rather than merely chat or display charts. Capabilities include:
- Live portfolio view (space, costs, utilization, effectiveness for people).
- Addition of commute times, transit access, and team sentiment.
- Lease performance insights, location scoring, optimization strategies, automated abstraction, renewal/expiration tracking.
- Scenario modeling for supply/demand rebalancing.
- Market research and location strategy (talent, demographics, amenities, infrastructure).
- Predictive elements (attendance forecasting, anomaly detection).
- Decision tracking: why a choice was made, whether it held up, and recommended next steps.
Architecture emphasizes enterprise readiness: SOC 2 Type II, per customer model training (no data pooling), own ML infrastructure, support for open source LLMs, and abstraction for external providers. Agents are designed to work alongside teams, handling data gathering and analysis while humans retain judgment.
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Named customers include Meta, Uber, Merck, and Cohesity. A Meta executive (Dave Gunter, VP of Global Workplace Services) has publicly endorsed the platform as purpose built AI that “thinks about the problem the way we do, not just another dashboard.”
CRE is typically the second largest enterprise expense after payroll. Hybrid work, cost pressure, utilization scrutiny, talent location strategy, and sustainability goals have made it more strategic, yet tooling has lagged legal, HR, and finance. Trebellar targets this gap with vertical AI that turns fragmented operational data into continuous, actionable intelligence rather than static reports or generic BI.
The raise validates demand for specialized AI agents in complex, data heavy, high stakes operational domains that general purpose tools have not fully addressed. Blossom’s lead (and Ophelia Brown’s public comments on the category and team) signals confidence that CRE requires purpose built technology rather than repurposed dashboards or services. Continuity of seed investors (Haystack, Alt Capital) plus new capital supports scaling beyond early design partners.
Near term focus is product deepening (AI agents and ontology), team expansion, and enterprise go to market. Longer term potential lies in making CRE a continuously updated, AI reasoned dataset that accelerates decisions on portfolio optimization, workplace experience, cost, and location strategy, shifting the function from periodic analysis and consultant dependence toward internal, real time capability. The combination of strong technical founders, marquee customers, domain advisor talent, and vertical specificity positions Trebellar to capture a meaningful share of the emerging AI native CRE software category.
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