| Criterion | Audiree | OCR / document-AI APIs (Nanonets, Doxis AI.dp) |
|---|---|---|
| What you get | A finished workflow: reading, contract matching, checks, review queue, per-job dashboard | Extraction (and workflow building blocks) you assemble into your own process |
| Line-level delivery note reading | Yes — article, quantity, unit, price | Yes — Doxis lists line items, dates and docket numbers for delivery notes |
| Match lines to a contract price book by meaning | ✓ | You build it |
| Construction checks (price × qty, units vs m², D16 vs D22, rebar tonnage) | ✓ | You build them |
| Cross-check against POs or invoices | Against the contract, delivery notes and invoices | Doxis: “can cross-check delivery note data against purchase orders or invoices” |
| Review queue for site and accounts | ✓ | You build it (Nanonets offers a workflow builder) |
| Capture from site | Photo in the site’s chat group, PDF or email | API, low-code platform; Doxis offers a mobile scanning SDK for your own app |
| Needs developers | — | ✓ |
| Public pricing | On request, by volume of documents and jobs | Nanonets: $50 free credits, then $100/month for 100 credits; blocks $0.02 / $0.10 / $0.30 per run. Doxis: tailored quote (both checked 2026-09-29) |
Compiled from public sources on the date shown. If something has changed, tell us and we will correct it.
When OCR / document-AI APIs (Nanonets, Doxis AI.dp) is the better choice
- You have developers and only need extraction — an OCR API is cheaper than a finished product.
- You are a software company embedding delivery note OCR in your own app; Doxis offers an API and a mobile scanning SDK for that.
- You process many document types beyond construction and want one extraction layer you control.
- Your matching logic is unusual and you’d rather own it in your own code.
When Audiree is the better choice
- You don’t have (or don’t want to spend) developer time building matching, checks, review screens and dashboards.
- You want construction rules working from day one: contract price × quantity, unit consistency, bar designation, rebar tonnage tolerance, wrong-contract detection, duplicates by document number and supplier.
- Site management and accounts need one place to review and decide, not a JSON output.
- Your jobs are in Portugal and your documents are guias de remessa and faturas.
What does an OCR API give you?
Document-AI APIs read a file and return structured data. Doxis AI.dp (ex-Klippa DocHorizon) describes delivery note extraction — date, docket number, buyer, quantities and line items — through a low-code platform, an API or a mobile scanning SDK, with output in JSON, XML or CSV; it states ISO 27001 certification and EU hosting, and says it can cross-check delivery note data against purchase orders or invoices. Pricing is a tailored quote (checked 2026-09-29).
Nanonets is a horizontal document processing and workflow builder. Its pricing page (checked 2026-09-29) lists a Starter plan with $50 of free credits, then $100/month for 100 credits; usage priced per block run at $0.02, $0.10 or $0.30; Growth and Enterprise plans on quote. It notes a typical invoice workflow runs 4–6 blocks per document.
What do you still have to build?
Extraction answers “what does this document say?”. A construction check needs more:
- A contract price book per job, and the logic to match “BET C25/30” on the note to “Concrete C25/30 XC2 S3” in the contract.
- The arithmetic: line price = contract price × quantity, document total vs sum of lines, positive quantities.
- Construction traps: units vs m², D16 vs D22, rebar invoiced in tonnes vs bars counted on site, wrong contract referenced.
- Duplicate detection by document number and supplier.
- A review screen where site and accounts see the exact difference and decide, plus audit of who approved what.
- Dashboards: contracted vs invoiced per job, pending exposure, returnable pallets, month-by-month breakdown.
Rule of thumb
If your team can build and maintain those pieces, an OCR API is the cheaper route. If not, the cost is in the months of building, not in the per-page price.
How Audiree does it
A photo of the delivery note (or a PDF or email) is read by AI in two independent readings; every line — article, quantity, unit, price — is matched to the job’s contract price book by meaning, and ten deterministic checks run. What matches is approved automatically; divergences go to a review queue with the exact difference. Read more in delivery note OCR and construction invoice matching software.
Built in Portugal
Audiree is built in Portugal and works today with Portuguese construction companies. Reading is layout-agnostic, so suppliers’ documents from other markets can be read as they are, and we run demos with your own delivery notes and contracts — but we don’t claim local compliance outside Portugal.
Which route should you take?
Build on an API if you have developers, only need data out of documents, or are embedding extraction in your own product. Use Audiree if the goal is to stop checking delivery notes and invoices by hand on construction jobs and you want that working without a software project.
Frequently asked questions
Is Klippa the same as Doxis?
Klippa’s delivery note OCR page now presents the product as “Doxis AI.dp (ex-Klippa DocHorizon)” (checked 2026-09-29).
How much does Nanonets cost?
On 2026-09-29 its pricing page listed a Starter plan with $50 of free credits, then $100/month for 100 credits, with block runs at $0.02, $0.10 or $0.30; Growth and Enterprise on quote. Check the page for current prices.
Isn’t an OCR API cheaper than Audiree?
For extraction alone, usually yes. The difference is the matching, checks, review queue and dashboards you would have to build and maintain on top.
Does Audiree offer an API?
Audiree is a finished workflow with a platform for site and accounts and CSV export for Excel. It is not sold as an extraction API.