Privacy-first: audit your field data without transferring it

When you offer to audit field data, the first objection is almost never the price. It’s: “we can’t send you our beneficiary data.” And that’s entirely legitimate — GPS, phone numbers, health, contractual data: handing that to an unproven vendor is a real risk.

Dalili’s answer isn’t to reassure with promises. It’s to reduce the demand to share to zero, by adapting the audit mode to your confidentiality level.

Six ways to audit without exposing everything

• Anonymised — you strip names, phones and identifiers before sending. The quality audit doesn’t need them to measure reliability.
• Sample — 50 to 500 rows are enough for a first diagnostic. No need for the whole database.
• On-site — processing runs on your machine or network, with no copy leaving.
• Local Audit Toolkit — a binary you run yourself: dalili audit file.csv → a PDF report, zero upload. Your data never leaves your machine.
• Self-hosted — Dalili runs on your servers (Docker), for institutions that want full control.
• Secure SaaS — once trust is established: encryption, roles, audit logs, DPA.

Why it’s a selling point, not a constraint

Most tools ask: “send us your data.” Dalili asks: “choose what you show us.” For an M&E team or an NGO handling sensitive beneficiary data, that inversion changes everything — it lets them test the value before extending their trust.

And the audit engine is decoupled from the cloud: the same logic runs as a service or locally, with no difference in result. Privacy-first isn’t an afterthought; it’s an architecture decision.