Densery

Comparisons

The vendors you are actually shortlisting.

If you are evaluating this category you are looking at three or four names and an internal build. Rather than let a review site tell you how we compare, here is our own account — including the cases where you should not buy from us.

THE CLOSEST STRUCTURAL ANALOGUE

Densery vs Hyperscience

The incumbent for on-premise and air-gapped document processing, with FedRAMP High and government references. The comparison is not about deployment — both run inside your walls. It is about whether the output is data or completed work.

Read the comparison →
THE DEFAULT SHORTLIST ENTRY

Densery vs ABBYY

Three decades of OCR intellectual property and an analyst incumbency that puts them on the list automatically. Strongest on multilingual and handwriting. The question is what happens after the page is read.

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THE IN-VPC ARGUMENT

Densery vs Instabase

Tier-one bank deployments and a platform that runs in your own cloud tenant, answering the residency objection without hardware. The difference is what you have to finish yourself.

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THE COMPETITOR THAT USUALLY WINS THE MEETING

Densery vs building it in-house

Free at the margin, fully in-perimeter and politically favoured. It is also the option that fails most often. Here is the honest arithmetic, including when you should ignore us and build.

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ALSO WORTH YOUR TIME

If you are earlier than a shortlist, the ranked overview of the on-premise document AI market is the better starting point — it covers eight vendors including the ones we lose to. On-premise document AI in 2026, ranked →

How to read these pages

We wrote the case against ourselves too.

A comparison page written by a vendor is worth exactly as much as its worst paragraph about itself. So each of these says plainly where the other company is the better buy, and what Densery does not yet have — a US customer we can name, a FedRAMP authorisation, an analyst placement, and a support organisation the size of theirs.

If you find a claim here you can disprove, tell us and we will change the page. That offer is not rhetorical: hello@densery.com.

THE ONE-LINE VERSION
  • Hyperscience — if you need FedRAMP High today, buy Hyperscience
  • ABBYY — if the job is extraction across many languages, buy ABBYY
  • Instabase — if in-VPC is enough and you have engineers, look at Instabase
  • Build it yourself — if you have 30+ ML engineers, build it
  • Densery — if the work must be completed and evidenced, inside your walls

The next step

Ninety minutes, your documents, three numbers.

A scoping session is not a demo. Bring twenty real files, redacted if you need to. We take three numbers off you — annual volume, fully loaded cost per file today, and what happens when the output is wrong — and hand back a one-page value case in your own KPIs.

If the arithmetic says we are not a fit, we will tell you in the room rather than six weeks later.

Book a scoping session Work out the number first
QUALIFY YOURSELF OUT

We are a fit if all three are true

  • More than 250,000 pages a year, or 25,000 claims or files
  • A legal obligation — regulator, board risk committee or parent-company policy — to keep the data in-house
  • An AI or agent pilot that did not reach production

If your data can go anywhere and your documents are already clean and digital, you do not need us. Use a hyperscaler document API and spend the money on something harder.