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Affinda
Document AI platform for production extraction across invoices, resumes, onboarding packs, and many other document types, with natural-language setup and API embedding for products. Affinda raised A$25 million at a A$220 million valuation in February 2026, led by Toll Group founder Paul Little.
Product and ops teams that need document parsing across many formats with a faster configuration path and an API they can embed.
Agencies that require FedRAMP High on day one, or buyers who only need a multi-agent workflow canvas.
Verdict
Affinda is a good fit when you need production document extraction without standing up a year-long IDP program. Customer stories emphasize invoice, logistics, and recruitment documents with measurable cuts in manual entry. Practitioners like setup speed and document breadth; the heaviest regulated enterprise packets may still favor Hyperscience-class platforms.
Score Breakdown
How Affinda scores in the categories that matter to its buyers.
The Field at a Glance
How Affinda compares with other Document intelligence / IDP vendors we reviewed, by Overall Score and relative typical engagement cost.
Affinda scores 6.6 in Document intelligence / IDP, under Extend (7.9), Reducto (7.9), Hyperscience (7.8), and Indico Data (7.7). Relative cost lands mid-band for this subcategory.
Compared with …
- Affinda vs Hyperscience 7.8/6.6
- Affinda vs Indico Data 7.7/6.6
Use-case matrix
| Use case | Fit | Notes |
|---|---|---|
| Multi-type document parsing | Strong | Wide document catalog. |
| Natural-language workspace setup | Strong | Stated Affinda Agent path. |
| API embed for products | Strong | Common recruitment/fintech use. |
| FedRAMP High public-sector suites | Weak | Hyperscience holds FedRAMP High authorization. |
| Complex claims packets at huge scale | Mixed | Hyperscience targets large claims and onboarding packets. Affinda’s published cases center on invoices, logistics and recruitment. |
| GPU inference compilers | Poor | Affinda does not sell GPU inference software. |
Review Excerpts
Excerpts from public reviews and forum discussions of Affinda, plus representative buyer views drawn from public information. Paid reviews and pay-for-play sites were excluded.
“There are excellent commercial AI resume parsers already - Affinda.com being one. Not expensive and takes minutes to implement.”
“We send resumes and invoices through the API and map the output into our applicant tracking and ERP systems.”
Representative buyer view
“Teams with strict audit and deployment requirements will find fewer published enterprise references than at larger IDP vendors.”
Representative buyer view
Where customer reviews couldn't be found, our analysts attempted to give a voice to buyer sentiment, drawing on real information from review sites, forums, and product documentation.
Based on: Affinda’s website
Company Facts
- Founded
- 2012 (CB Insights)
- Headquarters
- Melbourne, Victoria, Australia (CB Insights)
- Total funding raised
- $32.92M, including a A$25M (about US$17.7M) round in February 2026 at a A$220M valuation (CB Insights, Australian Financial Review)
- Key investors
- Paul Little, Ashok Jacob, Greg Ellis, Mark De Ambrosis, Nick Speer, John Russell (CB Insights)
- Website
- affinda.com
Key Leadership
Tim Toner
Co-founder and CEO
Methodology
This page is an independent evaluation of Affinda for buyers comparing options in Document intelligence / IDP. AI Industry Reviews accepts no sponsorships, advertising, or pay-for-placement fees. Affinda did not pay for this review.
What we scored
The headline number is an Overall Score on a 0-10 scale. Eight criteria fall under it in two groups.
- Buyer outcomes (for Document intelligence / IDP)
- Document parsing accuracy
- Setup speed / natural-language config
- Breadth of document types
- API / product embed path
- Company & commercial
- Innovation & product leadership
- Project management & communication
- Pricing
- Contract fairness
Pricing measures whether the price looks fair for the value delivered, including packaging and renewal friction that show up in real buying cycles.
Score Composition
| Input | Weight | What it covers |
|---|---|---|
| Reviews | 40% | A proprietary read of what practitioners say about likes, complaints, and day-to-day use, including public review sites, forums, and private chat rooms. Paid reviews and pay-for-play sites are out of scope. |
| Product | 35% | Hands-on look at screens and workflows. |
| Pricing | 15% | Whether the price looks fair for what you get. |
| Docs & training | 10% | Docs, tutorials, and training material. |
How we balanced the evidence
The Overall Score is the simple average of the eight criteria. Recommendation language follows that score and the use-case matrix above.
Scope
Affinda is graded here as Document intelligence / IDP. Criteria scores can move as more review volume and product checks are added.