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Picking & Packing app vs ParcelNow 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: Picking & Packing app (2025 – 2026) → ParcelNow (2025 – 2026) → Pairly (Jul 2026 – present)
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Picking & Packing app ›
A Kotlin warehouse app for fulfilment teams
ParcelNow ›
On-demand parcel delivery with real-time tracking
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
- Technical lead, Smart Kitchen Co
- When
- 2025 – 2026
- Length
- 1 yr
- Status
- Delivered
- Type
- Web, Platform
- 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.
Customer and operations dashboards with backend services for parcel lifecycles, tracking events and notifications, built for high-throughput transactional workflows.
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
- Next.js
- FastAPI
- PostgreSQL
- Redis
- Docker
- Python
- FastAPI
- PostgreSQL
- Redis
- Next.js
- React
- Azure
- LangChain
- Docker
Highlights
- Led architecture and development
- Built in Kotlin for warehouse floor use
- Next.js dashboards over FastAPI services
- Live delivery updates through logistics and messaging integrations
- 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
—
- Docker-based development and deployment standards
- 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.