Orbital lands $60M Series B to overhaul real estate legal workflows
Orbital, a legaltech startup building artificial intelligence specifically for real estate law, has raised $60 million in a Series B funding round led by Brighton Park Capital. The company said the new financing brings its total funding to $75 million and will be used to accelerate its expansion in the United States following the opening of a New York office last year.
Additional investors participating in the round include REV (the venture arm of RELX), JLL Spark, Seedcamp, and Grosvenor, according to details shared in the announcement.
Targeting a massive market with stubbornly manual processes
Real estate is frequently described as the world’s largest asset class, with estimates placing its value at roughly $140 trillion. Despite that scale, much of the legal work that underpins transactions—title review, contract analysis, risk identification, and the reconciliation of maps and historic property records—remains heavily manual.
Orbital is positioning its platform as a way to reduce time spent on document-heavy due diligence and to lower the risk of costly errors. The company’s approach combines document automation with spatial mapping and property data, aiming to give lawyers and deal teams a faster way to interpret what a property’s documentation says and how that maps to the physical, location-based reality of the asset.
From satellite imagery to real estate legal AI
The company was founded in 2018 by co-founders Will Pearce and Ed Boulle. Pearce said the business initially worked with satellite imagery and real estate data before the recent boom in large language models reshaped the AI landscape.
As the product evolved, the team focused on where automation could have the most impact in a sector known for complex, high-stakes paperwork. Pearce argued that legal professionals can spend days reviewing hundreds of pages to find specific risks, a process he described as inefficient for firms and costly for clients.
He also emphasized that real estate legal work is not solely about interpreting text. It often requires connecting fragmented records, local jurisdiction rules, old maps, and historical deeds to understand how rights and restrictions apply to a particular parcel of land. That location-based complexity, he said, makes real estate distinct from other categories of legal work and a poor fit for generic tooling.
How the platform works
Orbital says its AI is purpose-built for real estate and trained on legal documents and location-linked datasets. The company highlights several core capabilities:
- Automated contract review with linked supporting documents
- Interactive property maps to visualize relevant spatial constraints
- Dashboards designed to flag risks quickly
- Support for identifying UK and US title issues
- Collaboration tools for multiple stakeholders in a transaction
- Integration into existing workflows used by title and real estate investment teams
Pearce said a key part of the company’s strategy is domain specialization, including employing team members with direct experience practicing real estate law. He framed that expertise as central to building models that can perform reliably in a field where edge cases, local rules, and historical records can materially affect a deal.
Specialization over general-purpose legal AI
While broad legal AI platforms have gained traction across multiple practice areas, Orbital is differentiating itself by narrowing its scope to real estate. The company argues that the mix of text-based legal analysis and spatial reasoning—tying documents to maps, boundaries, and jurisdiction-specific constraints—creates a specialized problem set that benefits from tailored data and workflows.
What the new funding will support
With the Series B, Orbital plans to expand further across the U.S. market and deepen its product offering across the “entire asset lifecycle,” according to the company. Pearce said the longer-term goal is to build a single, secure workspace that connects parties involved in transactions who typically operate with fragmented information and disconnected systems.
Real estate deals often involve law firms, title companies, brokers, surveyors, and lenders—each working from different documents, sources of truth, and timelines. Orbital is betting that consolidating these workflows into a shared system can reduce delays and improve reliability, particularly when risk identification depends on reconciling many versions of the same underlying facts.
Broader implications for real estate and legal services
The funding underscores continued investor interest in vertical AI products that focus on high-value, process-heavy industries. Real estate legal work is a natural target: transactions are large, timelines are sensitive, and mistakes can be expensive. If automation can shorten diligence cycles while improving consistency, it could shift how firms price work, how quickly deals close, and how risk is surfaced to clients.
The company did not disclose valuation or additional financial terms of the round. A request for comment on diversity and inclusion initiatives was not answered by the company at the time of publication, according to the original report.
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