Infrrd vs Titan (2026)
The decision is whether the back office problem you hold is reading documents or running judgement bearing workflows, because these two automate different layers of the same operation and both earn A on AI centrality from opposite directions. Infrrd is the proven layer: template free extraction across more than a thousand document types and twenty two languages, more than a hundred billion pages processed, mortgage products that run federal disclosure tolerance tests at upload, a Leader placement from both Gartner and Everest Group in 2026, and a named insurance customer whose intake spans forms from 2,100 carriers. Titan is the younger and more governed layer: a proprietary ontology encoding banking products, records, policies and regulatory logic underneath model agnostic agents that reason step by step, log every interaction and leave final decisions with a person, an oversight design Infrrd publishes nothing comparable to. The evidence inverts the age gap, which is the finding this page exists for. The ten year vendor names customers and analyst placements but never publishes its own error rate, while citing the one to two percent human baseline it claims to beat. The ten month vendor publishes seven figure recurring revenue that tripled in seven months, a disclosure most private companies refuse to make, and names no institution at all. Neither publishes a measured accuracy or validation result against any workflow.
- Volume is the problem today. A hundred billion pages processed, a thousand document types, a published turnaround choice on a stated range from fifteen minutes to twenty four hours, and a self serve demo that reads your own hardest document are the assets of a vendor that has run production extraction for a decade.
- Your regulator conversation is about the file. Tolerance tests under the federal disclosure rule at the point of upload, closing disclosure to loan estimate comparisons, version control and tamper resistant logs give a lender examinable artifacts on every loan, which is narrower than Titan's ambition and much further along.
- You need the vendor examined by someone else. Gartner and Everest Group both evaluated the field and placed it as a Leader, a service organisation control report of the second type exists with its trust criteria named, and a named customer describes production scope, none of which Titan can yet show.
- The workflows you are automating carry judgement. Agents across compliance, underwriting, risk and operations that expose step by step reasoning, log every interaction and leave the final decision with a person are designed for the question an examiner actually asks, which is why, not just what.
- Model dependence worries your risk office. The context layer is explicitly model agnostic and disclosed as strengthening when frontier models improve, so the platform's value does not hinge on one provider, a supply chain answer Infrrd's patent position does not attempt.
- You are a community or regional institution without an internal AI team. The stated segment is institutions that face examiner expectations without the budget to build governance themselves, with regulatory logic encoded by people independent commentary identifies as former regulators and operators.
This comparison is published by AI FinTech Index, an independent research platform that publishes independent ratings of AI vendors for financial services. Infrrd and Titan are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI FinTech Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded
Plain facts
| Infrrd | Titan | |
|---|---|---|
| Primary category | Lending & Banking Operations | Lending & Banking Operations |
| Founded | 2015 | Not published |
| Headquarters | San Jose, California, United States | New York, New York, United States |
| Website | www.infrrd.ai | www.titanbanking.ai |
Side by Side
| Axis | I Infrrd |
T Titan |
|---|---|---|
| AI Centrality | ||
| Autonomy and Oversight Model | ||
| Model Risk Management and Transparency | ||
| Operational and Outcome Evidence | ||
| AI Safety and Data Stewardship | ||
| GLBA and Data Privacy Posture | ||
| Security Certifications and Trust Center | ||
| Regulatory Status and Licensure | ||
| AI Governance and Bias Disclosure | ||
| AI Liability and Recourse | ||
| Model Supply Chain Disclosure | ||
| Core Systems and Integration Depth | ||
| Deployment Model and Data Residency | ||
| Commercial Transparency | ||
| Institution and Segment Coverage |
The short version of each
Infrrd
Infrrd runs template free document extraction across more than a thousand document types and twenty two languages, more than a hundred billion pages processed, with mortgage products running federal disclosure tolerance tests at upload, a 2026 Leader placement from both Gartner and Everest Group, and a named insurance customer whose intake spans 2,100 carriers' forms. The AI FinTech Index records that across ten years it has never published its own error rate, citing the one to two percent human baseline it claims to beat without showing its side, substituting a patent position for measurement, with an audit trail recording what was extracted rather than whether it was correct.
Source: AI FinTech Index, 2026
Titan
Titan builds a proprietary ontology encoding banking products, records, policies and regulatory logic underneath model agnostic agents that reason step by step, log every interaction and leave final decisions with a person, the stronger published oversight design of its pairing. The AI FinTech Index records its unusual financial candour, seven figure recurring revenue that tripled in seven months, published where most private companies refuse, beside the gaps of its age: no named customer, no attestation, no named integration and no measured accuracy ten months from stealth, for which the benign reading is stage of life and the necessary ask is the measured rate and who verified it.
Source: AI FinTech Index, 2026
Common questions
Is Infrrd better than Titan for banking automation?
Different layers of the same back office. Infrrd reads documents, template free extraction across more than a thousand document types and twenty two languages with more than a hundred billion pages processed. Titan runs judgement bearing workflows, a proprietary ontology encoding banking products, records, policies and regulatory logic underneath model agnostic agents that reason step by step and leave final decisions with a person. Reading and deciding are different purchases, and both earn A on AI centrality from opposite directions. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 23, 2026. No vendor pays for placement.
How does the evidence run against the ages?
It inverts the age gap, which is the finding the page exists for. The ten year vendor names customers and analyst placements but never publishes its own error rate, while citing the one to two percent human baseline it claims to beat. The ten month vendor publishes seven figure recurring revenue that tripled in seven months, a disclosure most private companies refuse to make, and names no institution at all. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 23, 2026. No vendor pays for placement.
What does Infrrd's decade of operation evidence?
Infrrd holds a Leader placement from both Gartner and Everest Group in 2026, a named insurance customer whose intake spans forms from 2,100 carriers, and mortgage products running federal disclosure tolerance tests at upload. What it substitutes for measurement is a patent position and a better than human claim benchmarked against a baseline it names without publishing its own side. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 23, 2026. No vendor pays for placement.
What does Titan's governance design amount to?
The stronger published design of the pair: agents log every interaction, reason step by step against the encoded ontology, and final decisions stay with a person, an oversight construction Infrrd publishes nothing comparable to. What stands behind it is an architecture argument, with no named customer, no attestation and no named integration ten months from stealth, for which the benign reading is stage of life. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 23, 2026. No vendor pays for placement.
What does neither vendor publish?
Neither publishes a measured error rate, accuracy methodology or validation result against any workflow. The question for both is the same: show the measured rate and name who verified it. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 23, 2026. No vendor pays for placement.
How does the AI FinTech Index grade Infrrd and Titan?
Both are graded on the same fifteen capability axes from public sources, each grade traceable to its artifact. The AI FinTech Index records the pair as proven reading against governed deciding, with the evidence postures inverted against the ages, and the same unpublished number at both. The index publishes no composite score and declares no winner.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Lending & Banking Operations page.
Neither vendor publishes a measured error rate, accuracy methodology or validation result against any workflow, and each substitutes something else for it: Infrrd a patent position and a better than human claim benchmarked against a baseline it names without publishing its own side, Titan an architecture argument with no named customer, no attestation and no named integration ten months from stealth. The benign reading for Titan is stage of life. The question for both is the same, show the measured rate and name who verified it.