Kompato AI vs Skit.ai (2026)
The license against the layer. Both encode Regulation F as operating code rather than policy, including the seven contacts in seven days cap, and they sit on opposite sides of the buyer's operation. Kompato AI replaces it: a licensed collection agency running on generative agents, unscripted outbound negotiation, portfolio analysis scoring accounts by repayment likelihood and selecting channel and timing per debtor, outcome only fees with nothing charged where nothing is collected, and SOC 2, PCI DSS and ISO 27001 held. Skit.ai deliberately does not. It is an autonomous voice layer positioned over the collections platform a creditor already runs, with compliance resolved before the number is dialed. Eligibility, consent and timing are settled up front, accounts are filtered against do not call registries, bankruptcy filings, statute of limitations and known litigators, and every drafted line is screened before the consumer hears it. Each publishes a different honesty. Kompato states its automation split plainly, 96.4 percent of queries resolved against 3.6 percent escalated to humans, with scale from ten thousand to over a million accounts in 45 days. Skit publishes its process instead, a responsible AI evaluation naming bias and fairness testing and red teaming, staged rollouts under client sign off, and every engagement opening with a live production grade pilot on the buyer's own accounts. What they share is the shape of their evidence and its gap: both claim scale, a million accounts at one, a billion interactions at the other, and neither names a single customer institution. A structural asymmetry divides them: the licensed agency is positioned to answer who pays when an agent follows a rule wrongly and publishes no liability position, while the layer vendor states no position on the pending federal rulemaking that would govern the calls it makes.
- The operation moves out entirely. A licensed agency conducts the recovery, is itself accountable for conduct, and prices its compliance risk into outcome only fees, with no fee where nothing is collected.
- The automation level is stated. A published 96.4 percent resolution rate with 3.6 percent escalated tells a committee exactly how much of the work runs without a human, before any pilot is needed.
- Scaling is demonstrated operationally. Ten thousand to over a million accounts in 45 days, with portfolio scoring and per debtor channel selection, describes an operation built for volume placement.
- Your platform stays in place. A voice layer over the collections system you already run adds the conversation without a migration, which is the lighter deployment by design.
- Compliance resolves before the dial. Registry, bankruptcy, limitation and litigator filtering plus the Regulation F cap apply before anyone is called, and every drafted line is screened before the consumer hears it.
- The proof is generated on your book. A live production grade pilot opens every engagement, and the published responsible AI process, bias evaluation and red teaming named, gives a model risk function steps to examine.
This comparison is published by AI FinTech Index, an independent research platform that publishes independent ratings of AI vendors for financial services. Kompato AI and Skit.ai 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
| Kompato AI | Skit.ai | |
|---|---|---|
| Primary category | Customer & Banking Agents | Customer & Banking Agents |
| Founded | 2024 | Not published |
| Headquarters | United States | Not published |
| Website | kompatoai.com | skit.ai |
Side by Side
Select any grade to read the note behind it.
| Axis | K Kompato AI |
S Skit.ai |
|---|---|---|
| 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
Kompato AI
Kompato AI is a licensed collection agency running on generative agents, with unscripted outbound negotiation with payment plans and portfolio analysis scoring accounts by repayment likelihood and selecting channel and timing per debtor. It embeds the Fair Debt Collection Practices Act (FDCPA), the Telephone Consumer Protection Act (TCPA) and Regulation F's seven contacts in seven days cap as code, charges outcome only fees with nothing charged where nothing is collected, and holds SOC 2, PCI DSS and ISO 27001. According to the AI FinTech Index, it states its automation split, 96.4 percent resolved against 3.6 percent escalated, and scale from ten thousand to over a million accounts in 45 days. The gaps sit beside it. No customer is named, and no liability position is published, though as a licensed agency it is structurally positioned to publish one. Its three uplift figures do not reconcile and carry no baselines, and the data boundary with its consumer credit data science parent is unstated.
Source: AI FinTech Index, 2026
Skit.ai
Skit.ai supplies the conversation as a layer, autonomous voice agents positioned over the collections platform a creditor already runs, with statutory compliance resolved before the number is dialed. That covers registry, bankruptcy, limitation and litigator filtering, the calling window enforced in the consumer's local time and Regulation F's seven contacts in seven days cap per account, and every drafted line is screened before the consumer hears it. According to the AI FinTech Index, its evidence design is a live production grade pilot opening every engagement, so the buyer's own book generates the numbers, beside a published responsible AI process naming bias and fairness evaluation and red teaming. Open items remain. No customer is named behind a stated billion interactions, the named fairness process has no published result, and no model provider is named. It takes no position on the pending federal rulemaking covering the AI generated calls its product exists to make.
Source: AI FinTech Index, 2026
Common questions
Is Kompato AI better than Skit.ai for collections automation?
They are opposite purchases sharing one design idea. Both encode Regulation F including the seven contacts in seven days cap as code, and Kompato AI is a licensed agency that replaces your collections operation on outcome only fees, while Skit.ai is a voice layer that sits over the collections platform you already run. Placing the accounts or keeping the platform and adding the conversation is the actual decision, and the statute enforcement travels with either. 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 Kompato AI's license and fee model change?
Accountability and economics. A licensed agency is itself complainable about and sanctionable for conduct, and outcome only fees with nothing charged where nothing is collected put the agency's own money behind its compliance and recovery performance. The unfinished half sits beside the structure: positioned as it is to publish who pays when an agent follows a rule wrongly, Kompato publishes no liability position. 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.
Where does Skit.ai enforce compliance?
Before the number is dialed. Eligibility, consent and timing resolve up front, accounts are filtered against do not call registries, bankruptcy filings, statute of limitations and known litigators, the calling window is enforced in the consumer's local time, and Regulation F's frequency cap applies per account, with every drafted line screened in real time before the consumer hears it and each record scored and preserved afterward. 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 automation evidence does each publish?
Differently shaped automation figures. Kompato states its split plainly, 96.4 percent of queries resolved with 3.6 percent escalated to humans, plus scale from ten thousand to over a million accounts in 45 days. Skit publishes no containment figure and instead opens every engagement with a live production grade pilot, so the buyer's own book generates the number. A stated split against a generated one is the evidence choice. 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 publish?
Both claim scale and name no customer institution, which at a billion interactions and a million accounts reads as policy rather than youth. Neither names a model provider, neither publishes an error rate for the compliance machinery itself, Kompato's three uplift figures do not reconcile and its parent's data boundary is unstated, and Skit's named fairness process publishes no result, with no position stated on the pending rulemaking covering AI generated calls. 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.
Where does each publish the most, and the least?
Kompato AI publishes most on its license, its certifications and its automation split, and says little about liability, the models it is built on or the data boundary with its parent. Skit.ai publishes most on its compliance controls, its certifications and its responsible AI process, and says little about customers, fairness results or the models it is built on. 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.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Customer & Banking Agents page.
Both claim scale and name nobody, a million accounts in 45 days at one, more than a billion interactions at the other, so references at either come from the sales call rather than public material. A structural difference divides them: Kompato holds the license and prices recovery risk, so it could publish who pays when an agent follows a rule wrongly, and does not, while Skit, whose product is the call itself, states no position on the pending federal rulemaking covering AI generated calls.
Kompato's three uplift figures on the same measure carry no baselines and do not reconcile, and its parent, a consumer credit data science business, leaves unstated whether collections payment behavior informs the parent's scoring. Skit's fairness process is named but unquantified, no evaluation result is published, and neither vendor names a model provider or publishes an error rate for the compliance machinery itself. Both hold the same certification set, SOC 2, PCI DSS and ISO 27001.