Orbital Raises €50 Million in Series B to Scale AI for Real Estate Legal Work

Orbital, a London and New York based artificial intelligence platform specialising in real estate law, secured €50 million (about $60 million) in a Series B funding round. The capital will support expansion in the United Kingdom and United States, and accelerate development of software tailored to complex legal workflows in property transactions.

Context on Orbital and Market Position

Orbital develops AI designed specifically for legal processes in real estate, a segment historically resistant to automation and dominated by manual document review and contextual interpretation. The company was founded in 2018 by Will Pearce and Ed Boulle and was previously known as Orbital Witness before simplifying its brand in 2025 to reflect broader product ambitions.

The platform combines machine learning with spatial data and document analytics to interpret interdependent records, historic deeds, and mapping information that underpin property transactions. Users include law firms, in-house legal teams, developers, title companies, and real estate investment trusts. Orbital supports hundreds of thousands of transactions annually across the US and UK.

Orbital secures €50M to scale its domain-specific AI for property legal workflows.

Details of the Series B Round

The funding round was led by Brighton Park Capital, a US-based growth equity firm focused on software and tech enterprises. Additional participants included REV (the venture arm of RELX, the company behind LexisNexis Legal & Professional), The LegalTech Fund, Moderne Ventures, and Grosvenor Group. Existing backers such as JLL Spark, Outward, and Seedcamp also invested. Brighton Park’s Kevin Magan will join Orbital’s board.

Total funding raised by Orbital now stands around €63 million (roughly $75 million) since inception. Customers span large international law firms including AM Law 100 and Magic Circle practices, as well as multinational corporations.

Mechanics of Orbital’s Technology

Orbital’s platform addresses the inherent complexity of real estate legal work by using domain-specific AI trained to interpret and organise documents, maps, and property datasets. This approach contrasts with broader legal AI tools that are typically general purpose. The technology aims to reduce manual review burdens, surface legal risks earlier, and link disparate data into structured outputs.

The product suite includes tools for visualising property boundaries, extracting insights from legal records, and generating structured reports. Adoption has grown alongside an industry imperative to improve transparency and efficiency in a market where many core processes have changed little in decades.

Sector Funding Trends

Orbital’s Series B sits alongside a broader pattern of investment in legal technology, particularly AI-driven offerings. While most funding in 2025 and early 2026 has been concentrated at earlier stages, a few larger rounds such as Sweden’s Legora Series B highlight rising investor interest in domain-focused solutions. Smaller rounds across European LegalTech underscore diversification of capital but also the relative scale of Orbital’s raise.

Implications for Legal and Real Estate Workflows

The infusion of capital positions Orbital to expand its footprint and product capabilities. The emphasis on domain specificity underscores a strategic shift among investors toward platforms that integrate AI into existing professional workflows rather than generic automation tools. Expansion in the US, following a New York office launch in 2025 and planned additional hubs, reflects competitive pressures in the largest legal services market in the world.

By embedding AI into previously manual processes, the technology could influence how risk is assessed and communicated in property deals. This trend may pressure traditional legal service models to adopt similar tools or risk losing efficiency advantages. The move also reflects broader investor belief that specialised AI can address long-standing structural challenges in large but fragmented markets.