Case Studies

A Toronto law firm with a strong real-estate practice engaged Aruvi to advance practical AI adoption. The initial expectation was a broad readiness assessment. The first working session revealed a different reality: the firm already had an HTML CRM backbone tied to a live spreadsheet. The highest-leverage move was therefore not a multi-month diagnostic, but a focused module that sat on what already existed.

We built a Lead Generator that runs entirely on the firm’s network. Common campaign language (“purchase in the last two years,” “over age 40,” “with email”) is handled by fast deterministic filters in milliseconds. A local Ollama model is used only when natural-language interpretation is genuinely required. No bulk client data leaves the firm’s environment. The MVP was designed, hardened, and deployed with live data, a double-click launcher, scenario library, and operating documentation. The result is a usable tool that strengthens the firm’s own backbone rather than creating a side AI island. Deliberate architecture over spectacle.

Intenora is Aruvi’s own product: a personal alignment system that connects a North Star to monthly goals, daily actions, reflection, and six life areas the user defines. The challenge was not another task list, but a working loop that people can actually open on a phone or laptop.

The product was taken from concept through authentication, cloud data, payments, and production. The live stack uses Firebase Hosting and Authentication, Cloud Firestore with per-user security rules, Stripe for annual and lifetime access, Google Calendar integration via Cloud Functions, and a responsive tracker with Health Metrics and State Management. Development was accelerated with Grok Build; architecture, testing, and product judgment remained human. Access unlocks only after Stripe confirms payment. Cloud sync is the point of the account, not an afterthought.

The case demonstrates that a consulting practice can translate a real need into a signed-in, paid, production application, and that AI shortens the distance only when business analysis and process thinking stay in control.