A therapist-client platform with rule-based matching

Therapists running an independent practice juggle the same set of operational problems: scheduling across time zones, billing, sharing intake forms, tracking progress notes, and matching new clients to the right therapist on the team. Leena set out to consolidate that into a single platform serving both sides of the relationship.

The brief was a comprehensive build: therapist-side workflows (calendar, rescheduling, client roster, session notes, invoicing), client-side workflows (booking, profile, forms, progress visibility), and an intelligent matching layer that paired incoming clients to therapists based on specialty, availability, and stated preference.

The engagement ran as a fixed-scope AI Product Engineering build with a four-person engineering team: one senior and three mid full-stack engineers, paired with a product designer and a product owner.

Therapist-side surfaces cover calendar management, appointment-type configuration, billing, and a back-office admin panel for form management, session oversight, and client data. The client-side surface handles booking, intake forms, and session history.

The Match Flow algorithm pairs incoming clients to therapists. It is rule-based, not ML-driven: the system evaluates therapist specialties, availability windows, and the client's stated preferences, and returns the best fits. The strategy file is explicit that AI claims should not be retrofitted onto cases that did not ship AI features; Leena's matching is intelligent but not AI.

Tech stack: React with TypeScript on the frontend, Django and PostgreSQL on the backend, AWS for hosting, GitHub Actions for CI. Multi-time-zone scheduling support was built in from the start because the client roster spans regions.

Leena shipped as a working therapist-client platform with both sides of the workflow covered. No quantified user or revenue metrics are on file; Section 5 stays at the engagement-deliverable level rather than padded.