G2

Myra D.

Founder/CEO

Small-Business (50 or fewer emp.)

6/11/2026

"Accurate, Traceable Extraction Across Non-Standard Documents"

5/5

What do you like best about LandingAI Agentic Document Extraction?

Accuracy on documents that aren't standardized like paystubs from dozens of payroll providers, borrower-written letters of explanation, state IDs that vary by issuing agency. ADE handles formats it has never seen before without us needing to train or maintain a model. Second, every extracted value comes back with a confidence score and a citation to where it came from in the source document. In a regulated industry like mortgage, that traceability is the difference between an automation we can ship and one we can't. Review collected by and hosted on G2.com.

What do you dislike about LandingAI Agentic Document Extraction?

Per-document pricing is straightforward, but for high-volume customers it would help to have more granular cost forecasting tools from historical data. We track it ourselves but it's something we'd rather not have to. Review collected by and hosted on G2.com.

What problems is LandingAI Agentic Document Extraction solving and how is that benefiting you?

We needed accurate document extraction in a regulated industry. ADE handles non-standardized borrower documents — paystubs, letters of explanation, government IDs — with confidence scores and source citations on every field, against schemas we define. We integrated it via the in hours, not months. Accurate ADE has significant downstream effects and a directly impact on our business. Review collected by and hosted on G2.com.