AI & Agent Engineering
LLM-enabled systems, agent workflows, tool calling, authority boundaries, human approval and evaluation. Demonstrated through WorQ and AI PRO CRM.
Engineering
Engineering capability demonstrated by systems we operate.
We design for the point where software becomes operational: permissions matter, networks fail, data must reconcile, users need answers and a system still has to be maintainable years later.
Capability areas
Practical depth across systems and products.
Cloud & Platform Engineering
APIs, identity, permissions, deployment architecture, observability, resilience and platform modernisation across the portfolio.
Application Engineering
Android, iOS, Windows and web applications, cross-platform operational clients and device-aware workflows. Demonstrated through TableSync, PalletPOS and Shanai.
Commerce Systems
Point of sale, ordering, catalogues, stock, customer accounts, ecommerce and payment workflows. Demonstrated through TableSync AI and PalletPOS.
Fintech Engineering
Identity and KYC workflows, ledger architecture, wallets, provider integration and reconciliation through technology partnership work.
Data & Integration
APIs, webhooks, event flows, operational data, external-service integration, migration and governed access.
Engineering philosophy
Build for the operating consequences.
AI interprets. Business systems remain responsible for business truth.
Canonical data and transactional state remain in the system designed to own them.
Authority should be explicit.
Automated systems need defined scope, permissions and escalation paths.
Failure must be designed for.
Offline states, provider failures, invalid data and recovery are part of architecture.
Evidence is a product feature.
Important decisions and actions should leave enough context for later review.
Maintainability is delivery.
Documentation, observability and operational ownership are part of the finished system.