The founder of alphaAI Capital came to us with a bold vision: a consumer-friendly platform that blends AI, real-time ETF trading, and rich analytics—yet is simple enough for first-time investors. While they had a marketing landing page and some early designs, they also provided initial code. As part of the discovery process, we reviewed this code but ultimately chose not to reuse it due to its poor structure and inconsistent approach.
Key goals were to:
The platform had to execute real-time trades and show live dashboards, so performance and fault isolation were critical. At the same time, startup-level agility meant priorities changed fast; our process needed to pivot without breaking quality or deadlines.
We adopted iterative, micro-service development on Node.js and React, with Docker containers to isolate each integration. Server-side rendering in Next.js ensured sub-second load times for time-sensitive charts. Continuous demos and backlog grooming kept us aligned with new investor feedback and market shifts.
The core requirements for the alphaAI Capital platform are to deliver seamless onboarding (internal and Alpaca KYC), deposits and withdrawals via Plaid, subscription billing through Stripe, AI strategy deployment and simulation, real-time dashboards, statements & documents, referral tracking, marketing automation, and exhaustive logs and analytics.
We started with a focused Discovery Phase to transform alphaAI Capital ambitious vision into a clear, actionable roadmap. We conducted an in-depth code and integration review, analyzed the existing platform, and defined a strategic MVP and MDP scope with prioritized key features.
All core features (auth, trading, payments, analytics) were containerized from day one, supported by continuous delivery and bi-weekly sprints. This enabled smooth, secure, and rapid deployment of every new backlog item without trade-offs.