Project Case Study

REX — AI Business Operations Platform

Designed, managed and delivered end to end in a regulated industry, with compliance-driven architectural decisions. A production system demonstrating product ownership, technical project management, workflow automation, AI integration and enterprise systems thinking.

FounderProduct OwnerTechnical Project Manager

Technology Stack

Next.js · React · TypeScript · Node.js · PostgreSQL · Serverless Functions · REST & Webhooks · Large Language Model APIs · Scheduled Jobs · Object Storage · CI/CD

Executive Snapshot

Role

Founder · Product Owner · Technical Project Manager

Industry

Real Estate Technology (regulated)

Status

In production

Methodology

Agile / iterative, phased delivery

Team

Founder-led, full ownership

Architecture

Cloud-native, modular services

Deployment

Continuous delivery with preview environments

Integrations

12 external system categories

Focus

CRM · AI · Workflow Automation · Digital Transformation

10

Core modules delivered

CRM, automation, AI, communications, marketing, analytics, integrations, documents, scheduling, tasks — each listed in section 05

12

External system categories

Data feeds, calendar, email, messaging, voice, AI, mapping, advertising, social, media, storage, transactions — enumerated in section 09

5

Publishing platforms

Distributed from a single content pipeline with review before publish

12

Automated workflow rule sets

Assignment, follow-up timing, escalation, service-level tracking and send guardrails

8

Scheduled operations

Data ingestion, alerting, digests and housekeeping running unattended across both applications

148

API endpoints

108 in the operator platform, 40 in the public application

01 — Executive Summary

What REX is, and why it exists

REX is an operations platform that consolidates client management, automated workflow, AI-assisted work, multi-channel communication and analytics into one system. It was built to replace a set of disconnected commercial tools whose combined cost was significant and whose lack of integration forced the same information to be entered several times.

The operating environment is regulated: advertising standards, electronic-messaging consent law, and licensed data-distribution rules all constrain what the software may display, send and store. Those constraints were treated as binding requirements from the outset rather than as a compliance review at the end, and they materially shaped the architecture.

I own the product end to end: I define the roadmap, write the requirements, make the architectural and vendor decisions, run delivery, and perform acceptance testing. The system is in production use.

02 — My Role

Founder · Product Owner · Technical Project Manager

Accountable for outcome rather than for a single discipline. In practice this spans:

Roadmap & Release Planning

Defining phases, sequencing delivery against business impact, and deciding what ships versus what is deferred.

Requirements & Specification

Writing specifications with explicit, testable acceptance criteria — including non-functional and regulatory requirements.

Stakeholder Management

Running a short feedback loop with the end user, demonstrating increments and re-scoping on the basis of observed use.

Prioritisation & Scope Control

Maintaining the backlog, protecting the phase boundary, and recording the rationale when scope is cut.

Vendor & Technology Evaluation

Assessing providers on entitlement model, cost, data ownership and exit risk before committing.

Integration Planning

Defining module boundaries and the internal interfaces that keep vendor changes contained.

Risk Management

Maintaining the risk register and driving mitigation into design, particularly for compliance and third-party dependencies.

Quality & Acceptance

Verification against acceptance criteria before promotion, including deliberate negative testing of guardrails.

03 — Business Problem

Six disconnected systems, one operator

The pre-existing environment was a stack of independent subscription tools with no shared data model. The resulting failure modes were structural, not behavioural:

1Fragmented systems of recordClient information lived in several tools simultaneously with no authoritative source, so the same person could exist in three places in three states.
2Duplicated manual effortThe same information was re-entered per tool. Effort scaled linearly with volume, which put a hard ceiling on capacity.
3Poor operational visibilityNo consolidated view of pipeline or activity. Reporting meant manual assembly from several exports.
4Unautomated routine workFollow-up timing, task creation and stage progression all depended on human memory, so they failed under load — exactly when they mattered most.
5Fragmented communicationOutbound messages originated from several tools, each with its own consent handling, making a single auditable compliance position impossible.
6Compounding tool costMultiple overlapping subscriptions, each solving part of the problem and none solving the integration.

04 — Solution & Architecture

One data model, modular services

A single authoritative data layer with functional modules composed on top, and all external providers isolated behind an integration boundary. Components are shown at conceptual level; implementation detail is intentionally omitted.

Presentation LayerOperator Console · Public Web Application · Mobile-Responsive UIApplication LayerRouting · Authentication & Authorisation · Session & Consent EnforcementPlatform ServicesAI Services · Automation Engine · Communications · Document Generation · SchedulingData LayerRelational Store · Object Storage · Audit Trail · Access PolicyIntegration LayerProvider Adapters · Scheduled Ingestion · Webhook Receivers · Retry & BackoffExternal providers — data, communications, AI, calendar, mapping, advertising — sit beyond the integration boundary

Single source of truth

One authoritative record per entity, so every module reads the same data. Business impact: no reconciliation, no duplicate data entry, and one place to look for the truth.

One compliance checkpoint

All outbound communication passes a single consent gate. Business impact: the compliance position is provable rather than assumed, and it can't be bypassed by adding a new feature.

Contained vendor risk

External providers sit behind a consistent internal interface. Business impact: switching or losing a vendor is a contained change, not a rebuild — and cost is easier to control.

DashboardContactsPipelineTasksAutomationMarketingAnalyticsCalendarPipelineIllustrative dataActiveThis weekFollow-upsClosingNewContactedActiveOfferClosed

Illustrative layout only. Contains no real client, pipeline or business data.

05 — Core Modules

Capabilities and the business value each delivers

Client Relationship Management

A single record of every contact, interaction and stage, replacing spreadsheets and disconnected inboxes. Consolidated history means no one is contacted twice or forgotten.

Workflow Automation

Rules engine that advances work automatically — assignment, follow-up timing, stage changes and escalation — so routine coordination doesn't depend on someone remembering.

AI Services

Retrieval-grounded assistance for drafting, summarising and answering questions against live operational data, with explicit constraints on what the model may assert.

Communications

Unified outbound across email, SMS and voice with a single consent gate, so every message passes one compliance checkpoint regardless of which module triggered it.

Marketing Operations

Multi-channel content pipeline: scheduled generation, review-before-publish, distribution to several platforms, and performance attribution back to the originating asset.

Analytics & Reporting

Operational dashboards and a scheduled digest covering pipeline health, source performance and exception states requiring human attention.

Integration Layer

Adapters to external providers behind a consistent internal interface, so a vendor change is contained to one module rather than rippling through the system.

Document Management

Template-driven document generation and structured storage tied to the relevant record, with versioning and controlled distribution.

Scheduling

Calendar availability, booking and conferencing-link generation, synchronised bi-directionally with external calendars.

Task Management

Work items generated by system events with ownership, due dates and service-level tracking, surfaced by priority rather than creation order.

06 — Product Lifecycle

From problem statement to continuous operation

01

Idea & Problem Definition

Quantified the cost of the existing fragmented process — duplicated effort, tool spend, and the capacity ceiling it imposed.

02

Requirements

Written specifications with testable acceptance criteria, including binding regulatory and data-integrity constraints.

03

Planning

Phased roadmap sequenced by business impact, with explicit boundaries on what each phase would and would not include.

04

Design

Module boundaries, the shared data model, and the integration interface defined before implementation began.

05

Development

Incremental delivery on feature branches with preview environments, allowing review of each change in isolation.

06

Testing

Type and contract checks gating promotion, plus acceptance testing against the written criteria and negative testing of guardrails.

07

Deployment

Continuous deployment to preview on every change; promotion to production as a deliberate, reviewed step.

08

Continuous Improvement

Production observation feeding a maintained defect and enhancement backlog, with post-incident findings folded back into design.

07 — Project Management Practice

How delivery was actually run

1Requirements AnalysisTranslated operational pain points into written specifications with explicit acceptance criteria, including binding non-functional requirements for regulatory compliance and data integrity.
2Stakeholder ManagementOperated with the end user as primary stakeholder in a tight feedback loop — demonstrating increments, capturing rejection, and re-scoping based on observed use rather than assumption.
3Risk ManagementMaintained a register of technical, compliance and vendor-dependency risks. Highest-severity items were regulatory exposure and silent third-party failures; both drove design decisions rather than being logged and ignored.
4Backlog PrioritisationSequenced by business impact against delivery cost, with defects in revenue-generating paths pre-empting new feature work.
5Scope ControlHeld a documented phase boundary. Features that could not be delivered to a verifiable standard were deferred with the reason recorded, rather than shipped partially.
6Release PlanningTrunk-based delivery with feature branches, preview environments per change, and a gated promotion to production behind automated type and contract checks.
7User Acceptance TestingStructured verification against acceptance criteria before promotion, including deliberate negative testing of guardrails.
8Change ManagementDocumented decisions and their rationale in a maintained state-of-system record, so context survives between working sessions and is auditable after the fact.
9Continuous ImprovementPost-incident analysis fed back into the design — most notably converting silent failure modes into loud, observable ones.

08 — Technical Leadership

Decisions and their rationale

Managed platform over self-hosted infrastructure

For a small team, operational burden is the scarcest resource. Managed hosting and a managed database traded marginal cost for the elimination of infrastructure maintenance.

One language across the stack

A single typed language for both client and server removed context-switching and allowed shared models between layers, reducing a whole class of interface defects.

Relational store as system of record

The domain is inherently relational and the integrity requirements are strict. Referential integrity enforced by the database is stronger than integrity enforced by convention.

Adapters at the integration boundary

External providers are the least stable part of the system. Isolating them means a vendor change, entitlement change or outage is contained to one module.

Constrained AI rather than open-ended generation

In a regulated context an unconstrained model is a liability. AI features operate on retrieved live data with explicit prohibitions on asserting figures it cannot source.

Fail loudly, degrade gracefully

Following the silent-failure defect, scheduled work asserts on output volume, and user-facing surfaces render an empty state rather than a fabricated one.

09 — Integration Categories

External systems, described by category

Specific providers, endpoints and credentials are intentionally omitted. Each category below required its own authentication model, entitlement handling and failure strategy.

Licensed Data Feeds

Scheduled ingestion under licence terms governing what may be displayed, to whom, and for how long.

Calendar & Scheduling

Bi-directional availability and event creation with conferencing links.

Email Delivery

Transactional and bulk delivery with consent enforcement and deliverability handling.

Messaging & Voice

Programmable SMS and voice for time-sensitive notification, consent-gated.

AI & Language Services

Large-language-model services for retrieval-grounded assistance and content drafting.

Mapping & Location

Geocoding and location context for records lacking coordinates.

Marketing & Advertising

Campaign management and performance data, attributed back to originating assets.

Social Distribution

Multi-platform publishing and inbound interaction monitoring.

Media Generation

Automated production of video and graphic assets from structured input.

Cloud Storage

Object storage for generated documents and media, with controlled access.

Transaction Management

Integration with industry transaction systems for lifecycle status.

Analytics

Behavioural analytics and conversion tracking across public surfaces.

10 — Engineering Challenges

The hard problems, and how they were handled

1Integration complexityEach external provider brought its own authentication model, entitlement tiers, rate limits and failure semantics. Normalising them behind one internal interface was the largest single body of work.
2Silent failure in third-party dependenciesThe most instructive defect of the project: an upstream service answered a request with a success status and an empty payload because the credential used lacked entitlement to that data class. The job reported success indefinitely while importing nothing. It was found by asserting on expected row counts rather than trusting a success response — and the lesson generalised into how every scheduled job is now verified.
3Data integrity in a regulated contextDisplaying an unverifiable figure is a compliance exposure, not a cosmetic issue. The system was rebuilt to render a null state rather than a plausible-looking number whenever the underlying sample was insufficient.
4Workflow orchestrationScheduled work, event-driven work and user-initiated work all mutate the same records. Ordering, idempotency and preventing duplicate side effects required explicit design.
5Automated abusePublic intake endpoints attracted automated submissions that polluted the pipeline and triggered downstream notifications. Mitigated with layered heuristics that impose no friction on genuine users and fail open by design.
6Scalability and cost controlMetered AI and messaging services make an unprotected public endpoint a financial liability as much as a technical one.
7User adoptionThe system had to be measurably faster than the manual process it replaced, or it would be abandoned. Adoption was treated as an acceptance criterion, not an afterthought.

11 — Lessons Learned

What I would carry into the next delivery

A green status is not evidence

A process returning success proves the process ran, not that it did its job. Every scheduled job now asserts on the shape and volume of what it produced.

Prefer an empty state to a plausible one

A section that renders nothing is honest. A section that renders an invented figure is a liability that survives precisely because it looks correct.

Verify the credential, not just the connection

Authentication succeeding says nothing about entitlement. Access tiers must be verified against the specific data class the feature depends on.

The user's persistent complaint is a signal

Repeated feedback that something 'still looks wrong' was correct each time, and the underlying cause was consistently deeper than the visible symptom.

Compliance constraints improve the product

Rules that prohibit unverifiable claims force a discipline about data provenance that makes the whole system more trustworthy.

Instrument before optimising

Several assumed performance problems turned out to be truncation defects. Diagnostics were written before any tuning was attempted.

12 — Delivery Timeline

Phased delivery

Phase 1Discovery & RequirementsDocumented the operational workflow end to end, quantified duplicated effort, and defined the acceptance criteria and regulatory constraints the platform would be held to.
Phase 2Architecture & Vendor EvaluationSelected the platform stack and integration providers against criteria of cost, entitlement model, data ownership and exit risk. Defined module boundaries.
Phase 3Core PlatformDelivered the contact and pipeline foundation, the data ingestion layer, and the consent-gated communication path that all later modules depend on.
Phase 4Automation & AIIntroduced the rules engine, scheduled operations, and retrieval-grounded AI assistance with explicit constraints on model assertions.
Phase 5Marketing & DistributionAdded multi-channel content generation, review-gated publishing, and performance attribution back to source assets.
Phase 6Public Platform & HardeningDelivered the public-facing application, then ran a systematic audit of data provenance across every surface — removing unverifiable content and converting silent failures into observable ones.

13 — Capabilities Demonstrated

Skills evidenced by this delivery

Project ManagementTechnical Project ManagementProduct ManagementRequirements AnalysisBusiness AnalysisStakeholder ManagementRisk ManagementSystem IntegrationWorkflow AutomationDigital TransformationArtificial IntelligenceCloud ApplicationsSoftware DeliveryCross-functional LeadershipStrategic PlanningRegulatory ComplianceVendor EvaluationRelease ManagementData GovernanceSolution Architecture

14 — Technology

Stack, at a level I'm happy to discuss

Publicly discussable technology choices. Configuration, credentials, schema and proprietary logic are excluded.

TypeScriptReactNext.jsNode.jsPostgreSQLRelational Data ModellingREST & WebhooksServerless FunctionsScheduled Jobs / CronObject StorageRow-Level Access ControlLarge Language Model APIsRetrieval-Grounded AICI/CDPreview EnvironmentsGit / Trunk-Based DevelopmentResponsive Web DesignWeb Analytics

15 — Outcome

Where the platform stands

REX is in production. It replaced several standalone subscription tools with one integrated system, removed the duplicate data entry that capped operational capacity, and established a single auditable compliance path for outbound communication.

The most valuable outcome was not a feature. A systematic audit of data provenance across every user-facing surface found several cases where the system reported success while silently doing nothing, and others where unverifiable content was being displayed as fact. Correcting those, and rebuilding the verification approach so that class of defect surfaces immediately, did more for the platform's reliability than any individual capability.

Beyond the technical implementation, the project demonstrates the ability to translate business requirements into production software, integrate multiple technologies into a coherent system, manage delivery in a regulated environment, and continuously improve the platform through structured feedback and iterative releases.