The funding enables Conveyd to scale AI automation, cutting transaction times and costs for conveyancers, while positioning the company as a frontrunner in proptech legal services.
The UK property market has long grappled with slow, paperwork‑heavy conveyancing processes, creating a fertile ground for technology disruption. AI‑driven platforms are emerging as a solution, promising to streamline document verification, ID checks, and search requests that traditionally consume weeks of legal time. By embedding machine learning into each stage, these tools can reduce human error, accelerate approvals, and ultimately lower transaction costs for buyers and lenders alike.
Conveyd’s platform differentiates itself by combining purpose‑built AI with specialist lawyers to deliver an end‑to‑end service. Approximately 50 % of the conveyancing workflow—ranging from mortgage report generation to third‑party follow‑ups—is automated, allowing firms to shift from manual, time‑intensive tasks to rapid, data‑driven operations. The AI agents, trained to a trainee‑solicitor benchmark, produce review‑ready files that senior counsel can finalize, effectively creating a hybrid model that leverages both speed and expert oversight.
The recent £2.5 million seed round, led by prominent venture firms, provides Conveyd with the resources to expand its AI agent capabilities and scale across the UK’s fragmented conveyancing market. As investors pour capital into legal tech, the company is poised to capture market share from traditional firms resistant to change. Continued funding will likely accelerate product enhancements, broaden integrations with mortgage lenders, and cement Conveyd’s role in reshaping how property transactions are completed in the digital age.
London‑based AI conveyancing platform Conveyd announced a £2.5 million seed round, led by Eka Ventures with participation from Portfolio Ventures, Founders Factory and several angel investors. The funding will accelerate development of AI agents to automate key stages of the conveyancing process.
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