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Picking & Packing app vs WhatsApp platforms vs Pairly
The problem, what was built, the stack and the outcome, next to each other.
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In common
- Shared stack: none in common
- Order: WhatsApp platforms (2018 – 2022) → Picking & Packing app (2025 – 2026) → Pairly (Jul 2026 – present)
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Picking & Packing app ›
A Kotlin warehouse app for fulfilment teams
WhatsApp platforms ›
Altur, Harambee and eButler on the WhatsApp Business API
Pairly ›
An AI-native operating system for founder-led teams
At a glance
- Role
- Lead, Smart Kitchen Co
- When
- 2025 – 2026
- Length
- 1 yr
- Status
- Delivered
- Type
- Mobile
- Role
- Lead engineer, Mmogo Media
- When
- 2018 – 2022
- Length
- 4 yr
- Status
- Delivered
- Type
- Platform, AI
- Role
- Founder / Lead Engineer
- When
- Jul 2026 – present
- Length
- 4 mo so far
- Status
- In progress
- Type
- AI, Web, Platform
The problem
An Android app that drives picking and packing for warehouse and fulfilment operations.
A WhatsApp-based job platform (Altur), Harambee Youth Accelerator's move from a mobisite to WhatsApp, and eButler's WhatsApp ordering with payments through Flash.
Small teams stitch together disconnected tools for websites, customer communication, content, analytics and operations, while generic AI assistants lack safe access to business context and actions.
What was built
—
—
Pairly gives each business one governed platform where specialised agents can work across those functions. It combines tenant-scoped AI agents, websites and CMS, CRM and communications, newsletters, analytics, integrations and a skills marketplace.
Stack
- Kotlin
- Android
- Python
- Django
- WhatsApp Business API
- Infobip
- Twilio
- Python
- FastAPI
- PostgreSQL
- Redis
- Next.js
- React
- Azure
- LangChain
- Docker
Highlights
- Led architecture and development
- Built in Kotlin for warehouse floor use
- Conversational journeys on the WhatsApp Business API
- Payments via Flash, Paystack and MTN MoMo
- Tenant-scoped agent runtime with durable memory, model routing, typed tools and permission ceilings
- Streaming agent UX with human approval gates, audit events and token budgets
- Installable skills marketplace with automated validation and human publication review
- End-to-end features spanning API, CMS, renderer, email and PDF output
Infrastructure choices
—
—
- PostgreSQL
Outcome
—
—
A broad working platform with multi-tenant permissions, real-time agent execution, publishing and revision workflows, provider integrations and installable skills, with approval gates, audit events and human review for consequential AI actions.