Practical systems integration and governed AI for UK universities.
Engineering analysis grounded in production deployments, official UK data, and institutional legacy realities — no vendor slideware, no speculative hype.
Flagship Technical Series
University Systems & Integration Architecture
In-depth guides for Higher Education CIOs, registrars, and enterprise architects modernising SITS, Salesforce, and VLE data pipelines.
Automating SITS:Vision Workflows: Practical Architecture for UK Universities
How to architect governed agentic workflows and integrations around Tribal SITS without risking database locks, Clearing downtime, or HESA data corruption.
Salesforce to SITS Integration: Event-Driven Patterns with Azure Service Bus
Architectural blueprint for resilient bi-directional synchronisation between Salesforce Education Cloud and SITS using Azure Service Bus, dead-letter recovery, and telemetry.
Connecting Canvas LMS into the Enterprise University Data Pipeline
Moving beyond fragile nightly batch CSV transfers: real-time Canvas API integration, LTI 1.3 standards, and automated coursework extension routing.
AI Governance for UK Higher Education: Protecting Sensitive Student Data
Navigating UK GDPR Article 9 special category student data, HESA statutory reporting, private Azure OpenAI enclaves, and human-in-the-loop oversight.
Field Playbooks
Written for the registrar's desk, not the engineer's
Decision-stage playbooks for HE leaders facing upgrade windows, audit scrutiny and slipping programmes — written to be forwarded internally.
The 90 Days Before a SITS Upgrade: A Playbook for Registrars & CIOs
A countdown for the highest-risk window in the university systems calendar — honest inventory, scope freeze, integration protection, rehearsed rollback and the stabilisation fortnight.
AI Automation That Survives an HE Audit Committee
The questions internal audit will actually ask — data residency, human approval, failure modes, exit costs — and the design patterns that answer them before the meeting starts.
Stabilisation Playbook: Regaining Confidence in a Slipping Programme
Why the reset instinct makes a troubled student-records programme worse — and the four-stage sequence (visibility, containment, trust, incremental delivery) that recovers it.
Foundational Research
Enterprise AI Architecture & Governance
Rigorous technical assessments comparing automation paradigms, evaluating private model enclaves, and analysing UK market adoption.
UK AI Adoption in 2026: What the Official Numbers Actually Say
Factual analysis of ONS, DSIT and DBT statistics tracking business AI adoption — the real rates, structural gaps, and operational imperatives.
RPA vs Agentic Automation: Where Each Actually Fits
A technical comparison of rule-based bots versus reasoning agents — why scripts break on exceptions and where LLM orchestration succeeds.
Deploying LLMs Without Sending Data to Public APIs
How to run private language models inside your own cloud tenant or on-premise hardware using open-weight models and governed Model Context Protocol tools.
Editorial Standards
Frequently asked questions about our research
Who writes and authors these technical insights?
All articles are authored by Brad McAllister, founder and technical director of Real Code Ltd. The insights draw directly from over a decade of hands-on delivery inside UK universities — including current architecture on the University of London Global Digital Campus and six-plus years managing student record systems at St Mary's University.
Are the architectural blueprints based on theoretical models or production deployments?
Every architecture described here is drawn from production environments. The event-driven Azure Service Bus patterns, dead-letter recovery queues, SITS database concurrency safeguards, and private tenant LLM enclaves are systems currently operating in production under rigorous academic and enterprise SLAs.
Can our university's IT strategy committee cite or reference these papers?
Yes. We publish these technical guides to help higher education IT leaders, enterprise architects, and data protection officers cut through generative AI marketing hype and evaluate practical, governed system integration.
Apply these architectural patterns to your university estate
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