Repository navigation
Add Regulatory Intelligence: From Notice to Action MicroHack - #579
Merged
Marco Weber (qxsch) merged 1 commit intoOct 28, 2026
Merged
Marco Weber (qxsch) merged 1 commit into
Marco Weber (qxsch) merged 1 commit into
Conversation
Digvijay (Digvijay)
force-pushed
the
feature/healthcare-regulatory-intelligence
branch
from
October 27, 2026 22:36
a3565ab to
24a6c5a
Compare
Author
|
This hack was requested by Joana and if you approve and merge it we can test it on the platform! Thanks in advance! /Digvijay |
A one-day MicroHack in which participants keep a fictional life-sciences company, Caldova Health Services, on top of regulatory change for its one medicine, Caldivex. - Challenge 1: a supplied Python monitor crawls fictional regulator and payer portals into a regulatory lake on Azure Blob Storage (de-duplication, versioning, paragraph citations, change events); Foundry IQ indexes it. - Challenges 2-5: four Microsoft Foundry prompt agents grounded in the lake: Document & Citation, Obligation & Impact Extractor, Regulatory Q&A and Executive Briefing, with a code-enforced human sign-off and audit trail. - Challenge 6 (stretch): an event-driven agent chain with the Microsoft Agent Framework in GitHub Codespaces, as supplied or written from a starter. - Coach walkthroughs with expected answers and troubleshooting from test runs, lab automation (Bicep, deploy-lab.ps1, dev/run-local.ps1), a devcontainer and 48 offline tests. Outside the lab folder: the hack's entry in 03-Azure/01-04-AI/Readme.md and its Codespaces configuration under .devcontainer/. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Digvijay (Digvijay)
force-pushed
the
feature/healthcare-regulatory-intelligence
branch
from
October 27, 2026 23:07
24a6c5a to
e10dfcc
Compare
Digvijay (Digvijay)
deleted the
feature/healthcare-regulatory-intelligence
branch
October 28, 2026 20:07
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
What this adds
A new MicroHack in 03-Azure/01-04-AI/11_Healthcare_Regulatory_Intelligence: Regulatory Intelligence: From Notice to Action.
Participants keep a fictional UK life-sciences company, Caldova Health Services, on top of regulatory change for its one medicine, Caldivex (tablets and an injection pen). Everything happens in the browser: the Microsoft Foundry portal and Azure Cloud Shell. The stretch challenge uses GitHub Codespaces.
Also included:
infra/main.bicep,labautomation/deploy-lab.ps1,lab-defaults.json, anddev/run-local.ps1to test it outside the platform.All regulators, payers, documents and dates are fictional training data stored in the lab.
Outside the lab folder
03-Azure/01-04-AI/Readme.md: one line for the new hack..devcontainer/03-azure-01-04-ai-11-healthcare-regulatory-intelligence/devcontainer.json: Codespaces only reads configurations at the repository root. It points at the lab's own Dockerfile.Verified
deploy-lab.ps1ran throughdev/run-local.ps1inresourcegroupmode. It produced all 10 dashboard values and the 12 role assignments in the lab automation README, followed by a monitor, knowledge base and agent smoke test.labautomation/README.md.impact-agentandbriefing-agentuse reasoning effort medium. A comparison of reasoning effort and temperature settings is in the Challenge 3 coach notes.