Dasseti vs Keye (2026)
Two ways to earn an institution's trust divide this page: Dasseti asks to be trusted because it was checked, and Keye because you can check. Dasseti, the manager selection exchange between allocators and the funds reporting to them, is this lane's assurance citizen, a named certification held, penetration testing stated, the model service it calls named on its own product page and committed to zero data retention, and that trust surface is part of why a client base holding twenty trillion dollars combined can adopt it. Keye, financial diligence on private equity targets, builds trust into the artifact instead: models read and structure while deterministic pipelines do the arithmetic, every figure carries its source, formula and supporting quote, and analyses export as spreadsheets with live formulas an analyst can audit, edit and reload without the vendor's cooperation, alongside a one sentence commitment, no retention and no training on customer files, that outdoes larger competitors. Then each vendor undermines its own method. Dasseti's accuracy is asserted as a quality, with no rate, benchmark or validation behind the flagging and generation its certified platform performs. Keye tops a genuinely strong verification architecture with the claim least likely to survive contact, describing output as one hundred percent error free, and that absolute sits in open conflict with an independent buyer's guide for its own category, which states plainly that no artificial intelligence tool runs a full quality of earnings because the analysis turns on judgement. Both cannot be right, and the vendor warrants nothing behind the description. The records complete the contrast, Dasseti's named clients beside unattributed numbers, Keye with no named customer at all. A buyer choosing between trust models should notice the irony: the checkable artifact comes without a certificate, and the certificate comes without a checkable rate.
- You select and oversee managers, not targets. Questionnaires, flagging, scoring, benchmarking and remediation on the allocator side, response management on the manager side, and the only direct integration into a major consultant database.
- Procurement needs paper you can hand over. A named certification held, penetration testing stated, and the called model service named and committed to zero retention.
- The platform spans the programme. Research management, fund review workflows, manager records, analytics and a sustainability module against the major frameworks.
- You diligence the target's numbers in your own medium. Raw deal files in any format become structured data cuts, cohort and margin analysis and anomaly detection, exported as spreadsheets with live formulas your team edits and reloads.
- Verification needs no vendor cooperation. Deterministic pipelines do the arithmetic, and every figure carries its source, formula and supporting quote.
- The data commitment is one sentence. No retention and no training on customer files, which outdoes the larger competitors in this niche.
This comparison is published by AI FinTech Index, an independent research platform that publishes independent ratings of AI vendors for financial services. Dasseti and Keye 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
| Dasseti | Keye | |
|---|---|---|
| Primary category | Capital Markets & Research AI | Capital Markets & Research AI |
| Founded | Not published | 2021 |
| Headquarters | Not published | New York, New York, United States |
| Website | www.dasseti.com | www.keye.co |
Side by Side
| Axis | D Dasseti |
K Keye |
|---|---|---|
| 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
Dasseti
Dasseti runs the manager selection exchange between allocators and the funds reporting to them, with digitised questionnaires, automated flagging, scoring and benchmarking, and it is this lane's assurance citizen: a named certification held, penetration testing stated, and the model service it calls named on its own product page with a zero data retention commitment, supporting a client base holding twenty trillion dollars combined. The AI FinTech Index notes the limit of each disclosure: the retention commitment covers the external model service rather than the platform, accuracy is asserted as a quality with no rate or validation behind the flagging that decides which managers get scrutinised, and its named references never join its quantified outcomes.
Source: AI FinTech Index, 2026
Keye
Keye runs financial diligence on private equity targets with trust built into the artifact: models read and structure while deterministic pipelines do the arithmetic, every figure carries its source, formula and supporting quote, and analyses export as spreadsheets with live formulas an analyst can audit, edit and reload without the vendor, alongside a one sentence commitment of no retention and no training on customer files. The AI FinTech Index records its headline claim, output one hundred percent error free, as sitting in open conflict with the independent buyer's guide for its own category, warranted by nothing and accompanied by no accuracy measurement, no certification an operational due diligence team can hold, no disclosed supply chain and no named customer.
Source: AI FinTech Index, 2026
Common questions
Is Dasseti better than Keye for investment diligence?
They serve different diligence and different trust models. Dasseti runs manager selection between allocators and funds, and earns trust by being checked: a named certification, stated penetration testing, a named model service committed to zero data retention. Keye runs financial diligence on private equity targets, and earns trust by being checkable: every figure carries source, formula and supporting quote, exporting as live formula spreadsheets an analyst audits without the vendor's cooperation. Allocators shortlist Dasseti; deal teams shortlist Keye. 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.
Can Keye's one hundred percent error free claim be trusted?
Read it precisely. It sits in open conflict with an independent buyer's guide for its own category, which states plainly that no artificial intelligence tool runs a full quality of earnings because the analysis turns on judgement. Both cannot be right, and Keye warrants nothing behind the description, publishes no accuracy measurement, and does not examine where the system degrades, such as inconsistent source formats or unusual accounting treatments. The verification architecture underneath is genuinely strong; the absolute on top of it is not. 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 Dasseti's zero retention commitment actually cover?
Its scope is the external model service named on Dasseti's product page, not the platform itself. No platform level retention schedule, processing terms or tenancy position is published, and nothing states whether the embedded inference carries an incremental charge. Keye's parallel commitment, no retention and no training on customer files, is clearer in one sentence than larger competitors manage, while its mechanism is equally undocumented. 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.
Does either vendor publish measured accuracy?
Neither publishes the number its method depends on. Dasseti asserts accuracy as a quality with no rate, benchmark or validation behind the flagging and generation its certified platform performs, and no account of how severity flagging is evaluated for tilt against smaller or non standard managers. Keye's absolute substitutes for a measured rate entirely. The checkable artifact comes without a certificate, and the certificate comes without a checkable rate. 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.
Who names customers?
Dasseti names an insurer, an institutional manager and a diligence provider, though its fivefold productivity figure attaches to nobody in particular, the recurring shape where the reference and the number never join. Keye names no customer at all. Neither publishes a price or a residency commitment. 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 Dasseti and Keye?
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 opposite trust models, trusted because checked against trusted because checkable, and notes that each vendor undermines its own method, Dasseti asserting accuracy without a rate and Keye claiming a rate no system can honestly hold. 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 Capital Markets & Research AI page.
Keye's absolute is the first thing to test: output described as one hundred percent error free sits in open conflict with an independent buyer's guide for its own category, which holds that no artificial intelligence tool runs a full quality of earnings because the analysis turns on judgement, both cannot be right, and the vendor warrants nothing behind the description, publishes no accuracy measurement, and does not examine where the system degrades, such as inconsistent source formats or unusual accounting treatments.
Its no retention commitment is clear while the mechanism is undocumented, no certification exists to hand an operational due diligence team, its supply chain is closed where the three comparable vendors in this lane disclose theirs, and no customer is named behind directional claims.
Dasseti's parallel gaps: accuracy asserted as a quality with no rate or validation behind flagging and report generation, the zero retention commitment covering the external model service rather than the platform, no published account of how severity flagging is evaluated for tilt, and named references that never join their quantified outcomes. Neither publishes a price or a residency commitment.