Sounds like a game‑changer. Let’s map the key data feeds first—weather, displacement flows, local supply chains—and then run a pilot in a smaller region to test the cost‑impact balance. We can bring in local NGOs for real‑time feedback and tweak the model on the fly. If we hit the mark, we’ll have a scalable tool that keeps people fed and the budget in check.

Great spot—data integrity is the backbone. I’ll start a quick audit checklist, flag any gaps, and line up our partners to get their feeds verified. Once we’ve cleared that, we can dive into the pilot and keep the budget lean while iterating fast.

Let’s roll: 1. Pull the audit checklist from the shared drive and run a quick scan—flag any missing metadata, timestamps, or source verifications. 2. Once we’ve got that green‑lit, sync the feeds into the staging environment—watch for format mismatches and run a sample data push to confirm ingestion. 3. Set the pilot window to a two‑week sprint, with daily check‑ins and a capped budget line of $5k. 4. Log every tweak in the shared logbook—note the change, the rationale, and the impact. That way, scaling later will be a straight copy‑paste of what worked. Ready to kick it off?