Fee-free investment platform for UK retail investors and SMEs
InvestEngine operates a Django + React Native stack serving over 100,000 UK retail investors with commission-free ISAs, pensions, and general investment accounts. The product roadmap signals a shift toward operational automation and compliance-first design: active projects span pension consolidation, financial crime monitoring, SME account redesign, and subscription tiers, while the pain-point profile (manual KYC/AML, regulatory complexity, onboarding friction) reveals a business scaling faster than its ops infrastructure. Leadership-heavy hiring in product and data reflects effort to reduce manual work and embed compliance into workflows rather than bolt it on post-launch.
Notable leadership hires: Product Head, Head of Product, Data Analytics Head
InvestEngine is a UK-based investment platform founded in 2019 offering fee-free ISAs, pensions, and investment accounts to retail investors. The platform provides access to curated ETFs from providers including Vanguard, Invesco, and J.P. Morgan. The company has grown to over 100,000 investors and recently expanded into SME business accounts and pension consolidation services. InvestEngine operates across the UK, Georgia, and the United States, with 51–200 employees split primarily across product, operations, and engineering teams. The architecture runs on Django and PostgreSQL backend with React Native mobile, backed by AWS infrastructure and observability tools (Amplitude, Mixpanel, GA4).
Django and Django REST Framework for backend, React Native for mobile, PostgreSQL and MySQL for databases, Redis for caching, AWS for infrastructure, and GitHub Actions + TeamCity for CI/CD. Analytics via Amplitude, Mixpanel, and Google Analytics 4.
Current projects include SME business account redesign, pension consolidation service, retirement income offerings, financial crime monitoring framework, subscription tier launch, and automation of CASS reconciliations and KYC/AML processes.
Other companies in the same industry, closest in size