Can you import our FlexiCapture document definitions?

Not today. Field sets, zones and validations are rebuilt here — the same work the Vantage path asks of you. What shortens it is blueprint provisioning and model-assisted template authoring: drop in a sample page, get a draft template with zones and data types, correct it, train it.

Is Tesseract going to lose against the ABBYY engine?

On degraded scans and dense forms, yes, measurably. That is why the hybrid path exists: Tesseract first, low-confidence words or pages re-read by a vision model. Settle it with a bake-off on your own documents — we publish the fields we lose.

We run ICR-heavy forms. Should we switch?

Probably not on that use case alone. Handwriting runs through the model path here, which carries a cost per page and a latency the traditional engines do not. We price it honestly rather than pretending the gap is closed.

Vantage has pre-trained skills. What do we get on day one?

A blueprint — finance, accounts payable, insurance, KYC, anti-money-laundering or supply chain — that provisions the project, workflow, routing, upload endpoint, export goal and a full field set in one action. That is a pre-authored field set, not a pre-trained model: you still author the template, with a model drafting it from a sample page. We would rather state that plainly than lose the pilot.

Can we run entirely offline?

Yes. Tesseract for text and a local GGUF vision model through a managed llama-server cover recognition with no outbound network. Vantage cannot run offline.

How does the cost curve actually compare?

Below roughly 100–150k pages a year, a metered platform is often cheaper than running infrastructure — we say so. Above it the gap widens every year, and for a service provider with twenty clients on one install it is not close.

Can you match its pages per hour?

Not as a blanket claim. Throughput here scales by adding nodes that declare the workflow duty, and the honest answer for any given box is a benchmark on your hardware and your paper. We run it before quoting volume.

Is your PDF/A really PDF/A?

The renditions assert PDF/A-2b with an sRGB output intent and PDF/A identification in XMP, built with PDFBox from stored page images and persisted word geometry. Archive buyers audit that claim, and we encourage validating a sample set with veraPDF as part of acceptance.

We already run TotalAgility for process automation. Why change capture?

You may not need to. The strongest shape is often capture here, feeding your existing orchestration through REST, JDBC, message bus or file drop — you keep the process estate and stop paying capture volume fees.

Does anything replace VRS?

The pre-processing chain covers deskew, despeckle, binarize, crop, line and punch-hole removal and colour dropout, ordered per project. VRS remains the benchmark on hostile paper; on ordinary departmental scanning the difference rarely survives a bake-off.

Do we have to draw a template for every supplier?

No. A template carries alternatives for layouts that differ, label search finds fields that move, and the model paths read documents you have not templated at all. Where a template does earn its keep is auditability: the same input produces the same output, and the field says which method produced it.

Can you learn from corrections the way Rossum does?

Templates train from operator corrections, and the verification hub's word-group mode applies one correction everywhere the same misread text appears. It is a different mechanism from a continuously retrained global model, and it stays inside your tenant.

We are happy with ChronoScan. When should we move?

When a second operator, a second client, an audit requirement or a compliance question arrives. Those are the four triggers we see — not features.

Is this overkill for one mailroom?

Possibly, and we will say so on the call. A single-machine install runs fine here, but if you will never need users, tenants, workflow or audit, the cheaper tool is the right tool.

Why would we leave a platform that works?

Usually one of three reasons: the renewal, a tenancy requirement Transact cannot meet, or a mandate to run models locally. If none of those apply, staying is a defensible answer and we will say so.

So you will not quote against ReadSoft for AP?

Not on SAP-native accounts payable with live master-data matching. We will quote for the other 70% of the documents in the building, and we will say the same thing on the first call as on the last.

Alternatives · Cloud OCR API

The Textract alternative for teams about to build a capture platform by accident.

Textract is frequently the real competitor in a build-versus-buy conversation: a team proposes Textract plus glue code instead of a capture platform. It is excellent at what it does. What it does not do is workflow, templates, validation, human review, tenancy, audit or export — which is the part that becomes an unowned internal product by year two.

See the hubs Compare the run rate Quote a bake-off

The honest read

They win

Recognition quality with zero operations and elastic scale
Pre-trained expense, ID and lending APIs
A bill that starts at nothing

We win

Being the platform: intake, workflow, templates, validation, review, tenancy, audit, export
Operator hubs that already exist, including a review UI you do not have to build
$0 per page after the hardware, with local models if you want them
One system to run instead of a Lambda estate nobody owns

Where we lead

The second year — when the glue code has become an internal product with no owner and the page bill has grown linear with volume.

KognitCapture vs Amazon Textract, side by side

Capability	KognitCapture	Amazon Textract
What it is	A capture platform	Five recognition APIs
Human review	Verification hub with zones, hOCR fill, validations, share links	Augmented A2I review loops you assemble
Workflow	Flow engine with routing, SLA and retention	Yours to build
Tenancy and audit	Native, per tenant	Yours to build
Cost	Flat licence plus your infrastructure	$1.50 per 1k pages text, $15 per 1k forms/tables

What each one costs to run

	KognitCapture	Amazon Textract
Licence shape	Flat platform licence, unlimited pages	Pay per page, no floor
Typical annual outlay	Infrastructure + your team	≈ $3k at 2M pages, text only
Marginal cost per page	$0 local · tokens only if you choose remote	$1.50 – $15 per 1k pages
Who runs it	You do, on your own hardware	You build and own the platform

Figures for Amazon Textract are published list bands and analyst-reported contract benchmarks checked in August 2026 — not quotes, and not vendor-confirmed. Your negotiated price will differ.

Switching

Keep Textract if you like it: it can sit behind the recognition step while this platform supplies everything around it. That is often the fastest way to stop the internal build without throwing away work.

Read the migration brief →

Questions buyers ask us about Amazon Textract

Our developers say they can wire this up in a sprint.

The recognition call, yes. The forty-odd capabilities around it — batch assembly, separator handling, template versioning, validation rules, an operator review UI, retries, retention, audit, tenant isolation, export mapping — are the sprint that never ends. Ask what happens when the person who wrote it leaves.

Can we use Textract as an engine here?

Recognition is pluggable and the plugin SDK exists for exactly this. Most teams end up local for volume and remote for the hard pages.

Next step

Send 200 pages. Get a field-level accuracy report.

Including the fields we lose on. That is the only comparison worth having against a two-decade incumbent.

A bake-off is a paid engagement at our standard consulting rate, scoped and quoted before it starts and running one to two days, two at most — not a free trial. The report is yours whichever way it lands.

Ask for a bake-off quote

Compare against something else

ABBYY FlexiCapture ABBYY Vantage FineReader Server Kofax / Tungsten Rossum ChronoScan Ephesoft Transact ReadSoft