Capture proof at the edge. Catch gaps before they become release, audit, or recall problems.
Onaply uses phone capture, AI reconciliation, and exception-first review to turn messy operational evidence into a proof chain your team can actually trust.
Capture labels, docs, and supplier proof where the work happens.
See what is broken before it turns into downstream chaos.
Keep humans in control of the calls that actually matter.
Snap pallet labels and lot labels on the floor
Capture COAs, receiving docs, and supplier paperwork in the moment
Push evidence into one chain instead of camera rolls and inboxes
Start reconciliation immediately instead of waiting for admin cleanup
The problem is not more data. It is broken proof.
Most teams already have the records somewhere. The problem is that the chain is fragmented, late, and hard to trust when pressure shows up.
Receiving proof is scattered across docs, photos, emails, and tribal knowledge.
Weak evidence shows up late, right when QA, audit, or release pressure hits.
Teams waste hours rebuilding the story by hand instead of acting on clear exceptions.
Put phone capture where it belongs: front and center.
Onaply should feel simple at the edge. Capture evidence fast, feed the system immediately, and let the app do the hard reconciliation work after that.
Capture what actually happened before it disappears.
Snap the label. Capture the COA. Upload the receiving doc. The goal is not pretty input. The goal is to get real evidence into one chain fast enough to keep trust intact.
Bring in pallet labels, lot labels, COAs, and receiving paperwork without waiting on perfect formatting.
Reduce lag between receiving activity and usable system truth.
Captured evidence goes into the active proof chain, not a dead attachment graveyard.
Handle variation, missing docs, and inconsistency like a real plant, not a clean demo.
A clean control surface for proof, not another pile of records.
The app should help operators understand what is ready, what is blocked, and what needs attention now.
One place for receiving docs, labels, photos, COAs, and supplier proof.
Link receiving, lots, batches, and supporting evidence into a reviewable proof chain.
Surface what is missing, what conflicts, and what needs operator review first.
Keep high-risk decisions with humans while the system prepares the proof.
Simple flow. Serious control.
Keep the story easy to follow: capture evidence, reconcile it, surface exceptions, and move forward with clearer release trust.
Use phone capture or uploads to bring messy field evidence into the system fast.
AI extracts, links, and checks records across receiving, lots, and batches.
Operators see exceptions, confidence gaps, and missing proof in one place.
QA and operations act with a clearer chain instead of rebuilding it under pressure.
AI does the ugly evidence work. Humans keep the important calls.
That is the right split. Extraction, linking, and exception routing should be fast. Release, accepted-risk, and other trust-sensitive calls should stay governed by people.
The system starts where evidence is created, not where paperwork finally lands.
Weak proof becomes visible early instead of hiding until release or audit time.
AI does the ugly evidence work. Humans keep the high-consequence calls.
Be ready for QA, audits, customers, and partners without the last-minute scramble.
Start with receiving-to-batch proof for food manufacturers dealing with messy supplier evidence.
Narrow enough to be clear. Painful enough to matter. Specific enough for the right operator to recognize immediately.