Atomic AoL was not built by a software vendor discovering accreditation — it was built inside accreditation, by people who live the AACSB process.
Atomic AoL began as graduate research on a concrete, unglamorous problem: Assurance of Learning reporting is some of the most repetitive, most expensive knowledge work in a business school. Faculty spend weeks each cycle compiling grades, chasing survey data, mapping learning outcomes by hand and re-writing narrative chapters that follow the same structure every time.
The research question was whether a multi-agent architecture — not a chatbot, not an assistant, but a pipeline of specialised agents, each with one job, one input contract and one output contract — could execute the workflow end-to-end while keeping humans in charge of every judgement that matters.
The answer is the platform you can run today: 41 agents in three layers, guarded by 25,500+ automated tests, with human approval gates on every consequential decision and a cryptographic audit trail on every output.
Designed and built the platform: the agent architecture, the analytics pipeline, the human-approval workflow and the signed-bundle format. Atomic AoL is also the subject of his graduate thesis on agentic AI systems for higher-education quality assurance.
Academic supervisor of the project at the Open University Business School, where he works on management education and programme quality. Giacomo keeps the platform honest: every feature must serve a real accreditation need, in language a Dean's office actually uses.
Whether you run one programme or a whole portfolio, we'd like to hear how your AoL cycle works today.
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