Omnitive Extract - Medical Claims
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 (17 more lines)
When it comes to processing personal insurance claims, it is typically one of the most time-consuming tasks to manually validate the information contained across the documents. To add on to the challenge, the processing window is typically short to keep up with market expectations. To facilitate this, TAIGER has trained Extract to pick up important data from both Singapore medical invoices (MI) and medical certificates (MC).
What should I expect?
The client whom we have implemented this project for has experienced* the following:
- 100% business rule accuracy
- 78% accuracy level in system performance
- 33% average time saved for processing (document accuracy)
- Note that every client’s experience differs, and the above figures are for references and not a commitment in any form.
The system is trained to extract the data points from medical invoice and medical certificates, if the data is present on the document. The following are the data points that the system is trained to extract:
- Medical Invoice
- Receipt/Invoice Number
- Claim Amount
- Receipt/Invoice Date
- Medical Certificate
- MC Number
- Clinic Name
- Start and End Date
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
3 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.

