AI-powered Web & Mobile Platform Development

Software Development Quotation Request AI-Powered Web & Mobile Platform — Full Production Build Project Overview We are looking for an experienced software development team or contractor to take an existing working prototype (MVP) through to a full, production-ready release. The product is a subscription-based platform — available as a responsive web app and as an Android app on the Google Play Store — that uses AI to analyse user-submitted conversations and provide the user with personalised feedback, guidance, and self-development tools based on that analysis. The core AI analysis engine and a working prototype already exist. This engagement covers building out the surrounding product: accounts, compliance, monetisation, localisation, an admin layer, and a set of deeper engagement and business features, as detailed below. Please note: to protect the underlying concept, this document intentionally omits the platform's name, branding, and specific market positioning. We are happy to share fuller detail, including a live demo, once a candidate has signed a short mutual non-disclosure agreement (NDA). Technical Context • Existing MVP is live and in use; this is an extension and hardening of that product, not a build from scratch. • Platform must work as a responsive web app across desktop and mobile browsers. • In addition to the web app, the platform must be available as an Android app distributed through the Google Play Store. Please propose your preferred approach (e.g. native Android build, React Native/cross-platform framework, or a wrapped/PWA-based build) and note any impact on cost or timeline. • Please include Play Store submission, review, and compliance requirements in your quote — including Google Play's Data Safety declaration, which will need to accurately reflect the sensitive personal data this platform handles. • Backend integrates with a third-party large language model (LLM) API for the core analysis, plus a separate speech-to-text service for voice input. • Data protection is a hard requirement throughout — the product handles sensitive personal data and must be built with GDPR compliance in mind from the ground up (not retrofitted). • Please propose the tech stack you would use or continue with, and flag anywhere you'd want to review our current implementation before committing to an approach. Scope of Work The sections below describe the functional scope. They are grouped by feature area for clarity, not by delivery order — please propose your own logical build sequence and timeline as part of your quote. 1. Core AI Analysis Engine The heart of the product: users submit a conversation (text or voice) and receive an automated analysis. • Secure, reliable pipeline for submitting a conversation (text input) and returning an AI-generated analysis in real time. • Voice input pipeline: record audio, transcribe to text via a speech-to-text API, then feed into the same analysis flow. • Five distinct analysis modules — each conversation is scored/evaluated across five separate dimensions, each producing its own structured output. • A clarification step: before finalising the analysis, the system should be able to ask the user one or more follow-up questions to improve accuracy, then incorporate the answers into the final output. • Automated safety/risk detection: the system must be able to detect sensitive or high-risk content within a submission and surface an appropriate warning/support banner rather than a normal analysis result. This needs careful, reliable handling as it is a safety-critical path. 2. Accounts, Onboarding & Platform Basics • Full authentication: anonymous/guest access, sign-up, sign-in, log out, forgot-password/reset flow, and email verification. • User history: each account should retain a record of past analyses, viewable by the user. • Onboarding flow for first-time users. • Account settings page. • Account deletion with full GDPR-compliant data erasure, plus a GDPR data export function (user can download their own data). • Proper error states, loading states, and analytics event tracking built in across the app (not bolted on later). • Full mobile responsiveness across every screen, not just the core flow. • Simple feedback mechanism on each analysis output (e.g. positive/negative/favourite-style reactions). 3. Localisation • A translation-file architecture that supports adding new languages without code changes to individual screens. • English live at launch, with two additional languages (one European, one East Asian) to be added during this engagement. 4. Admin & Internal Tooling • An internal admin dashboard for reviewing users, content, and platform activity. • An internal analytics dashboard covering usage and engagement metrics. 5. Monetisation • A payment/subscription system with upgrade prompts that surface premium features at the right moments in the user journey. • Please note whether your quote assumes a specific payment provider (e.g. Stripe) or if you'd like this specified. 6. Engagement & Retention Features • In-analysis follow-up chat: users can ask a follow-up question directly against a given analysis result. • One-tap suggested actions arising from an analysis. • Email notification system. • A scheduled follow-up/check-in system that prompts users to report back after a period of time. • Optional demographic profile collection during onboarding or later, for internal segmentation/reporting. • A personal progress-tracking dashboard showing the user their own history, trends, and patterns over time. • A full history view with pattern and growth-tracking visualisation. • Personalised short-form lesson content ('micro-lessons') generated or surfaced after each analysis. • An integrated, structured self-paced course (a linear sequence of lesson content delivered in-app). • A tone/emotion "translator" tool that helps rephrase or reinterpret the emotional tone of a piece of text. • A calendar/scheduling feature tied to the user's ongoing ac