Omnitive Extract - Hotel Bookings
Taiger Singapore Pte Ltd · Operations & Productivity
Certification per Microsoft Marketplace.
Evidence tier Source Confirmed · 7 captures on record
What the publisher says
As described on Microsoft Marketplace.
Extract is an Intelligent Reading tool that can read, understand and derive information from complex, unstructured data in any language or format. Using our proprietary Cleansing, Classification, Optical Character Recognition and Natural Language Processing capabilities, Omnitive Extract works well with both Hard-Copy (Scanned or Photo) and Soft-Copy documents. It processes heaps of document types to extract information that is most relevant to your business. In the past, we have process simple, Structured Documents (Ex. Passports), Semi-Structured Documents (Ex. Invoices), and Unstructured Documents (Ex. Annual Reports or Legal Documents) with >80% accuracy.
What is this solution?
Show the rest of the publisher’s description (13 more lines)
Despite tourism becoming increasingly challenging in 2020, hotels have remodelled their business to host quarantining. Irrespective of whether travel goes back to its 2019 boom or not, hotel bookings are a must to facilitate international travel. This solution enables quick and efficient reading and extraction from any English language hotel booking.
What should I expect?
The system is trained to extract the data points from any English language Hotel Bookings, if the data is present on the document. The following are the data points that the system is trained to extract:
- Hotel Name
- Check-In Date
- Check-Out Date
- Hotel Address
- Guest Name
Should you encounter any empty fields or “NA”, the following are some of the possibilities:
- Data point is not present on the document, masked/covered, noise (caused by handwritten text, stamps, etc).
- The model is not trained based on your sample document
Note: Unlike most capturing software out there, we do not use templates. The system is trained based on variances - the more varying documents the system is trained on, the more accurately it can extract any varying types of the document.
Reach out to the TAIGER team if you encounter any issues with the extraction or if you wish to understand how our technology works.
Preview
4 imagesAgent build and provenance
See the full provenance
The layer-by-layer build, the evidence behind each claim, the risk basis and the cross-marketplace links are open to any account. Some rows are disclosed, some the source leaves Unknown; a free account shows you which.
Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
Sources
Publisher resources
4 linksLinked repositories
Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.
Evidence risk is the share of the build you cannot see before you deploy, not a security rating. Sign in to see the layer-by-layer basis for this band.

