Rebzy Solutions · AI Systems & Workflow Automation

AI systems for real business operations.
Built to run without
babysitting.

Rebzy Solutions designs and builds production-grade AI systems, workflow automations, and business integrations that automate real operational processes.

Founded by Divine Ereba · Port Harcourt, Nigeria · Building for businesses worldwide.

HOVER TO INSPECT SYSTEM // LIVE Validation Human Review AI Agent CRM Payments Notifications Database Analytics

01 / Principles

How Rebzy builds AI systems.

Models are unreliable narrators. The system around them is what makes a workflow safe to run in production.

AI reasons. Code decides.

The model suggests. Fixed logic makes the call, so the same input gets the same outcome.

Deterministic validation before business logic executes.

Every input is checked against fixed rules before a workflow runs, so bad data never reaches production logic.

Humans stay in control.

High-stakes steps wait for a person to approve them. The system flags; it does not act alone.

Fail safely.

When a step breaks, the workflow stops in a known state instead of guessing what to do next.

Every workflow is observable.

Each run leaves a log: what triggered it, what it did, and where it stands now.

Reliability before intelligence.

A slower system that works every time beats a clever one that works most of the time.

Production over prototypes.

A demo proves an idea. A production system proves it can run unattended, for months, without you.

02 / Services

What we build.

AI agents & chat systems

Assistants that answer, route, and act, connected to your real data instead of guessing.

Workflow orchestration

Multi-step automations across the tools you already use, so work moves between them on its own.

Business process automation

The repeat tasks behind sales, support, and admin, rebuilt to run in the background.

Integration & API work

Clean connections between apps, payment systems, and databases, built to hold up under real traffic.

Engineering Decisions...

The parts that do not show up in a demo, but decide whether a system survives contact with real use.

Prompt injection protection

Inputs are sanitized and boundaries enforced, so a crafted message cannot hijack the agent.

Deterministic validation

Fixed rules check every output before it moves to the next step.

Structured outputs

Models return typed, schema-checked data, not free text to parse and hope.

Retry logic

Transient failures retry on their own, within limits, before anything alerts a human.

Human approval gates

Steps with real consequences pause for a person to confirm before they run.

Observability

Every run is logged and traceable, so a failure is easy to find and explain.

Error recovery

A broken step fails into a safe state and can resume without losing data.

Idempotent workflows

Running a step twice by accident does not double-charge, double-send, or double-write.

03 / Workflow

How it runs...

  1. 01

    Diagnose

    We map the current process step by step and find where time and accuracy are lost. No build starts before this.

  2. 02

    Design

    We plan the system on paper first: triggers, data flow, failure points, and what happens when a step breaks.

  3. 03

    Build

    We build in working slices you can see early, test against real data, and adjust before anything goes live.

  4. 04

    Operate

    We hand over documentation and logging, so the system stays clear to run and easy to hand off.

A typical request, end to end.

Our system follow this shape: validate before you trust, decide with code, and leave a record behind.

01User
02Webhook
03Validation layer
04LLM
05Deterministic checks
06Business logic
07CRM
08Notifications
09Logs

04 / Projects

Selected projects.

Explore production-ready AI automation systems built to solve real operational problems. Click a project for more details

AI Lead Qualification System
Real Estate

AI Lead Qualification System

Qualified, scored, and routed inbound property enquiries before they reached a sales agent.

Problem

Sales teams were manually reading enquiries, identifying buyer intent, and deciding who to contact first, leading to slow response times and inconsistent qualification.

Solution

Built an AI workflow that classifies enquiries, extracts structured data, scores lead quality, validates AI output with deterministic rules, and routes qualified leads directly into the CRM.

Key Engineering Decisions

  • LLM reasoning with deterministic validation
  • Structured JSON output enforcement
  • Prompt injection protection
  • Automatic CRM routing
  • Telegram alerts for high-value leads

Tech Stack

  • n8n
  • OpenAI
  • JavaScript
  • Airtable
  • REST APIs

Outcome

Reduced manual qualification while ensuring every lead entered the pipeline with validated, structured data.

Click to explore project →
AI Customer Support Platform
E-commerce Customer Support

Multimodal Customer Support Platform

Automated customer support across text, voice notes, images, and documents while keeping human agents in control.

Problem

Support agents spent significant time reading customer messages, interpreting attachments, updating records, and manually routing requests to the correct teams.

Solution

Built a multimodal AI support workflow that understands customer inputs, classifies requests, prevents duplicate tickets, updates the CRM automatically, and escalates complex conversations when needed.

Key Engineering Decisions

  • Text, voice, image, and document processing
  • Duplicate ticket detection
  • Structured AI response validation
  • Automatic CRM synchronization
  • Human escalation for edge cases

Tech Stack

  • n8n
  • Telegram
  • OpenAI
  • Google Sheets
  • JavaScript

Outcome

Reduced repetitive support work by automatically organizing customer requests while maintaining complete conversation history and operational visibility.

Click to explore project →
Invoice & Payment Automation
Finance Operations

Invoice & Payment Automation

Automated invoice generation, payment tracking, and financial notifications to eliminate repetitive accounting workflows.

Problem

Staff manually generated invoices, checked payment status, sent reminders, and updated financial records across multiple systems, creating delays and unnecessary administrative work.

Solution

Built an automated finance workflow that generates invoices, verifies payments, sends reminder notifications, updates business records, and synchronizes every transaction across connected services.

Key Engineering Decisions

  • Event-driven invoice generation
  • Automatic payment verification
  • PDF invoice generation
  • Retry logic for failed notifications
  • Complete transaction logging

Tech Stack

  • n8n
  • Paystack
  • PDFMonkey
  • REST APIs
  • JavaScript

Outcome

Removed repetitive finance administration, improved payment visibility, and created a reliable workflow for invoice creation and payment reconciliation.

Click to explore project →

05 / Technology

Technologies behind every workflow.

Production-ready automation is built by combining AI, software engineering, APIs, and reliable infrastructure into deterministic business systems.

Automation

n8n
Make
Zapier

AI

OpenAI
Claude
Gemini

Programming

JavaScript

Infrastructure

Docker
PostgreSQL
Git
GitHub

CRM

GoHighLevel
Airtable

Communication

Telegram
WhatsApp
Gmail

Payments

Paystack
Stripe

Integrations

Google Workspace
Notion
REST APIs
Webhooks

Contact

Every business has one routine that takes longer than it should.

Let's fix yours.