Production AI engineering, built on long engineering experience.
Radian IT has operated since 2005. The practice now focuses on moving AI workflows from prototype into controlled regular use, with the same architecture, integration, and operability discipline we bring to any production system.
What the practice focuses on
Production AI, end to end
The work runs from the workflow boundary through the production slice, evaluation fixtures, release controls, deployment handover, and a runbook the team can operate from.
The surrounding systems matter
Production AI workflows integrate with business systems, automation, data, reporting, and support tools. Those layers are part of the engagement, not an afterthought.
Evidence before rollout
A plausible demo is not proof. Evaluation fixtures, run evidence, and release gates decide whether a workflow is ready for regular use.
How we work
Plain principles that shape each engagement.
Useful software over slide decks
Advice is useful only when it leads to a clear decision or something that can be built.
Operable from day one
Checks, logs, approvals, recovery, and handover are part of the work from the start, not retrofitted.
Architecture that follows the business
System structure mirrors the business: clear ownership per capability, shared language, and a deliberate separation between the domain and its integrations.
Resilient integration
Systems are connected across asynchronous boundaries so long-running work is durable and failures stay local.
Open where it helps
Open-source tools are used where they make the work easier to inspect, move, and own.
Confidential by default
Client references kept anonymous and plural. Sectoral patterns described; specific organisations not named on this site.
Open for new engagements.
Email [email protected].