DigniFeed

Food-drive software designed around fair, consistent, and dignified distribution.

What it is

DigniFeed is a food-distribution platform in development for organizers serving people in need. Its focus is on the everyday work of a food drive: tracking inventory, understanding recipient preferences, and distributing limited resources consistently.

The intended workflow brings inventory, recipient preferences, and distribution planning together so organizers can make consistent operational decisions.

Who it is for

Food-drive organizers, volunteers, and the communities they serve.

The approach

Inventory and distribution tools for food-drive operations.
Preference-aware planning with fairness and consistency as design priorities.

DigniFeed, explained

Organizers retain distribution authority. Inventory and recipient preferences inform a human decision. DigniFeed’s intended role is explainable operations support, with uncertainty, exceptions and corrections visible.

1. Understand the stock record
An authorized operator starts with the approved organization and site. Quantity means little without a unit, condition and a source that can be checked for freshness.
Start with
A stock receipt or discrepancy within the operator’s permitted site.
What happens
Record or reconcile item, quantity, unit, condition and source/time.
Result
What is known, held or unresolved before anyone plans distribution.
No actual stock, donor, organization, recipient or current availability is shown here.
Sample operator workflow: stock context
Item, quantity and unit
Identify the item and measurement together; an unknown unit stays unresolved.
Source and time
Record where the quantity came from and when it was checked. Stale information remains visible.
Condition and hold
Distinguish held stock from stock an authorized person has cleared for planning.
Discrepancy
Flag a mismatch for reconciliation rather than inventing an available quantity.
Field structure only, not an inventory record or live-stock claim. Freshness belongs beside quantity.
2. Review preferences and options
An operator reviews minimal confirmed preferences alongside inventory constraints. Any assistance must explain its sources and uncertainty, not hide them behind a score.
Start with
Stock context and only the preference information needed for the task.
What happens
Examine options, constraints, freshness and exceptions before preparing a plan.
Result
An explainable proposed plan for a human to review, not an allocation decision.
No recipient needs, dietary or medical conditions, eligibility ratings or AI provider are invented.
Sample operator workflow: human-owned plan
Preference context
Use minimal confirmed information; do not infer needs or human worth.
Options and constraints
Keep stock units, holds and available evidence beside the proposed options.
Freshness and uncertainty
Explain missing or stale sources and why a suggestion may not fit.
Operator review
A permitted human chooses, overrides or asks for follow-up. Food-safety authority stays with authorized people.
A planning composition, not automated allocation. Receiving service need not require an online account.
3. Record the human decision
Keep the suggestion, reservation and confirmation distinct. An authorized operator decides what should happen; a reservation alone does not mean food was distributed.
Start with
A reviewed plan and stock whose rules allow the proposed action.
What happens
Record the human disposition, reserve within actual stock rules and confirm only when the human action is complete.
Result
An honest planned, partial, held or confirmed status, with a follow-up owner when needed.
This is not a completed distribution. Failed confirmation and offline entry cannot claim success.
Sample operator workflow: decision and status
Human decision
The authorized operator, not an AI suggestion, owns the disposition.
Reservation
A proposed hold must fit current stock rules; it is not confirmation or delivery.
Human confirmation
Record the actual action only after it occurs. A retry must not confirm twice.
Partial, held or failed
Keep unresolved status and the responsible follow-up role visible.
These are separate responsibilities, not records of an event that occurred. No autonomous distribution is supplied.
4. Correct and reconcile
When a discrepancy appears, an authorized person records a correction and its reason. Reconcile stock and preserve the follow-up state instead of silently rewriting history.
Start with
A discrepancy or exception in the recorded action.
What happens
Attribute the correction to the permitted operator and reconcile the affected record.
Result
An understandable correction with a reason, or an explicit need for follow-up.
Field labels do not establish an implemented audit trail, concurrency protection or successful recovery.
Sample operator workflow: correction structure
Correction and reason
State what changed and why the original record needs correction.
Attributed operator
Identify the permitted role responsible in the actual restricted record.
Reconciled stock
Check the effect on quantities, holds and pending actions.
Needs follow-up
Keep failures or unresolved discrepancies assigned to an authorized person.
No identity, date or audit entry is fabricated. Actual permissions and reconciliation rules remain product-owned.

AI assistance may help explain inventory, preferences and options; people decide distribution and exceptions. It must not rank human worth, silently deny service or guarantee fairness. Food-safety and site authority remain with authorized people. This public explanation contains no operational records, clinical advice or achieved-impact claims.

Research

What supports the proposed DigniFeed model, and what remains untested?

The evidence supports investigating whether food distribution can better accommodate household preferences and make operational decisions easier to understand and correct. It does not establish that AI allocation is necessary or that new software improves fairness, food security, nutrition, waiting time or waste.

Read the research