Legal tech platform for matter pricing, resource planning, and business intelligence
BigHand delivers software for law firms focused on operational visibility—matter pricing, lawyer utilization, and financial reporting. The engineering-led hiring (5 engineers, 2 leads) signals active platform modernization: projects span test automation, Kubernetes containerization, microservices maturation, and cross-product architecture, while pain points reflect legacy system debt (migrating to cloud, third-party data integration, regression test scalability). The stack is .NET + SQL Server on-premises pivoting toward cloud (Azure + AWS + GCP, Kubernetes, Docker) with Salesforce for go-to-market.
BigHand builds software solutions for legal professionals across matter pricing, resource and staff resourcing analytics, document production, and financial reporting. The platform targets law firms seeking to improve profitability, utilization tracking, and client experience. Founded in the United Kingdom with headquarters in London, the company operates with 201–500 employees and maintains a hybrid delivery model across the UK and Lebanon. Products are delivered as a portfolio; customers mix and match pricing, resource management, workflow, and business intelligence modules.
BigHand runs .NET + C# on SQL Server with Salesforce for CRM, deployed across Azure, AWS, and GCP. Infrastructure relies on Kubernetes, Docker, and Terraform; CI/CD is managed via Azure DevOps and Azure Pipelines.
Core projects include test automation (component, integration, e2e, performance), Kubernetes containerization, microservices maturation, cloud migration, and cross-product platform capabilities for pricing, resource management, and workflow products.
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BigHand'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.