Kastle provides AI agents for loan operations, from borrower questions and payment collection to new-loan qualification. It fits banks and mortgage servicers that need more support capacity without making every borrower wait for a human call-center agent.
What it does
Kastle’s current site positions AI agents across the full loan cycle and says the product is in production with ten of the top 25 U.S. servicers. The YC launch describes voice and SMS agents that collect payments, answer escrow questions, qualify inquiries, integrate with servicing and telephony systems, leave loan comments and route to live agents.
The product is more than a voice interface. A lender needs the agent to take an authorized action, write the right record and preserve the compliance trail. Kastle’s launch says it automatically scores calls against a lender’s quality framework. The public record also describes an AI employee for consumer lending, so the strongest fit is a defined loan-operation queue rather than unbounded financial advice.
The launch claims up to 90% call-center cost reduction; the current site displays a $24M Series A headline and production claims. These are company-published claims and should not be treated as independent cost or adoption results. Pricing is not public.
Founder context and tradeoffs
The YC profile identifies Rishi Choudhary as CEO, with mortgage-marketplace and product experience at Redfin, and Nitish Poddar as CTO, with backend inference and engineering leadership at Verkada. That founder context maps directly to lending workflows and customer-facing infrastructure.
The buyer should ask about payment authorization, borrower authentication, recording and retention, adverse-action boundaries, live-agent handoff, system-of-record writes and regulator-ready audit logs. The automation can reduce queue pressure, but it must be precise about what it is allowed to say and do.
Editorial take
I would shortlist Kastle for a servicer with high call volume, clear policies and a team that can review a narrow workflow. Start with one low-risk queue such as payment status or escrow questions, then expand after the system proves its handoff and audit behavior.
Quick facts
| Field | Sourced detail |
|---|---|
| Product | AI voice/SMS agents for loan servicing, payments and qualification |
| Buyers | Banks, mortgage servicers, lenders and sub-servicers |
| Public claims | Production with top servicers and cost-reduction claims, company-reported |
| Pricing | Not publicly listed |
| Main gate | Authentication, payment authority, compliance, system writes and escalation |
Sources checked
| Source | Checked |
|---|---|
| YC profile | 2026-09-19 |
| Kastle homepage | 2026-09-19 |
| Kastle launch | 2026-09-19 |
Cohort context
Kastle is listed in Summer 2024. In our 2026-09-18 directory snapshot, 161 of 248 listed companies in that cohort have YC’s primary industry label B2B (64.9%). This is a current-directory comparison, not an original intake count or a performance ranking. Nine-cohort dataset.
Public website snapshot
Observed 2026-09-19 16:17 UTC in raw homepage HTML. This records visible metadata and advertised links, not agent execution or product quality.
| Signal | Homepage observation |
|---|---|
| Product description metadata | Observed |
| Canonical link | Observed |
| H1 or H2 heading | Observed |
| Typed structured data | Not observed in this response |
| Docs/developer link | Not observed in this response |
| Pricing link | Not observed in this response |
| llms.txt link | Not observed in this response |
| Markdown alternate | Not observed in this response |
Public observations · Collection method. Missing links here do not establish that a capability or file is absent elsewhere.
