Legal tech platform automating property conveyancing and legal workflows in Australia
InfoTrack operates a SaaS platform for legal and conveyancing firms, built on a data-heavy stack (Snowflake, BigQuery, Redshift, Kafka) paired with .NET/React for application delivery. Active projects in settlement automation (Pexa integration), non-financial data architecture, and FP&A forecasting suggest the company is moving beyond point solutions toward end-to-end workflow and analytics capability. Current hiring is concentrated in support and operations, not engineering — a pattern consistent with a scaling SaaS business focused on customer retention and operational efficiency rather than platform expansion.
InfoTrack is a SaaS platform serving the Australian legal market, with a focus on property conveyancing automation and legal research workflows. Founded in 2012 and headquartered in Sydney, the company has built a client base of over 8,000 legal practices across Australia. The platform enables legal teams to search, analyse, organise, and communicate case and property information. The product surface includes online legal searching, manual conveyancing services, and integrations with third-party systems (Pexa settlements, Workday, DocuSign). The company employs 201–500 people and operates profitably as a privately held business.
InfoTrack runs Snowflake, BigQuery, and Redshift for analytics; .NET and React for application development; Kafka and Kubernetes for data pipeline orchestration; Salesforce and NetSuite for operations; and OpenAI API and Jasper for content generation. Security tooling includes Microsoft Sentinel, CrowdStrike, and Microsoft Defender.
Active projects include Pexa conveyancing settlement automation, non-financial data layer development, SaaS metrics analytics, and data pipeline work for Workday Adaptive Planning integration. Pain points centre on handling high-volume settlement files, order fulfilment delays, and scaling client service efficiency.
InfoTrack AU's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.