AI receipt suggestions.
You just confirm.
scan-ai does the first pass on every receipt — the business entity, a tax category and deductible percent per line, each with a confidence score. You review and confirm. Nothing is applied without you.
No credit card required · Cancel anytime
The work is mostly done by the time you look.
Every receipt arrives with the entity, the categories, and the deductible splits already filled in — and the soft spots marked. Your job is to glance, fix what looks off, and confirm.
A first pass on every receipt
On each scan, scan-ai suggests the business entity, a tax category, and a business-deductible percentage for every line item — each tagged with a confidence score so you know where to look first.
Duplicates caught and grouped
Forwarded the same Amazon confirmation twice? Snapped a receipt your accountant also has? scan-ai detects likely duplicates and groups them so the same expense doesn't get counted twice.
Bad photos flagged early
Blur, glare, an overexposed thermal slip — scan-ai flags image-quality problems on the spot, so you can re-snap before the receipt gets buried and the numbers go missing.
AI receipt suggestions you can actually trust.
A blurry $4.20 coffee gets a tentative guess; a clean Figma invoice gets a confident one. Every suggestion — the entity, the tax category, the deductible percent on each line — carries its own confidence score, so a low number tells you exactly where to spend your two seconds.
Nothing is final until you say so. The suggestion sits next to the receipt; you accept it, change it, or split a line, and that’s the recorded value. The AI proposes — you decide.
- Business entity suggested per receipt
- Tax category + deductible % per line item
- A confidence score on every suggestion
- Presented for confirmation — never auto-applied
Duplicates grouped, bad dates healed, blur flagged.
scan-ai catches the small errors that quietly wreck a year of books. It groups likely duplicate receipts so one dinner isn’t counted twice, and it self-heals ambiguous dates — spotting a DD/MM vs MM/DD transposition before 03/04 lands in the wrong month.
In chat you can go further: ask it to find spending anomalies or auto-categorize a whole batch. It shows you a preview of the proposed changes, and nothing is written until you confirm the step.
- Likely duplicate receipts detected and grouped
- Ambiguous dates self-healed (DD/MM vs MM/DD)
- Blur and overexposure flagged on the receipt
- Chat batch actions show a preview before you confirm
Once you confirm, it sticks.
Turn a confirmed suggestion into a standing rule so the next receipt like it lands sorted.
Every receipt mapped to a tax category and your own tags — override once, scan-ai remembers.
Ask chat to find anomalies or auto-categorize a batch — it shows a preview before any change.
Suggestions, plainly.
How does scan-ai suggest a tax category for a receipt?
On each scan, scan-ai proposes a tax category and a business-deductible percentage for every line item, and a likely business entity for the receipt. Each suggestion carries a confidence rating, so a low one tells you exactly where to look first. Nothing is recorded until you confirm.
Does scan-ai apply changes automatically?
No. Every suggestion is presented for you to confirm. You can accept it, change the category, adjust the deductible percent, or split a line, and your edit becomes the recorded value. scan-ai proposes, you decide.
Can scan-ai catch duplicate receipts and bad photos?
Yes. scan-ai groups likely duplicate receipts so the same expense is not counted twice, and you confirm or dismiss the group. It also flags image-quality problems like blur or overexposure on the receipt, so you can re-snap before the numbers go missing.
What does scan-ai do with an ambiguous date like 03/04?
When a parsed date lands in the future, scan-ai checks for a DD/MM versus MM/DD transposition and heals it to the correct day if the swap produces a sensible past date. If it cannot resolve the date safely, it leaves a fallback and flags the receipt for review instead of guessing.