Winter 2026

Kita

Underwrite borrowers around the world in minutes

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What they do

AI underwriting from messy documents for emerging-market lenders

How close to us

3, close

learning engine links document signals to repayment outcomes, so L3 loop; different buyer and domain

Wedges

  • No wedge fit written yet.
L1 Company brain (knows the organisation) 2, clear
L2 Agent team (runs agents, tools, approvals) 1, light
L3 Does and learns (finishes, checks, measures, updates the brain) 3, strong

Who buys

Firm size
not known
Buyer type
business
Role
lender credit and risk heads
UK
not known
Their own description (from YC)

In emerging markets, open finance is still nascent. Most of the population is traditionally unbanked, banking APIs don’t exist, and a borrower’s financial history lives in documents: e-wallet records, bank statements, utility bills, and more. Because this data is unstructured, credit and risk teams are forced into manual review. This slows decisioning, increases costs, and caps lending volume.

Kita is the AI platform for global lending operations. We help lenders in emerging markets automate application completion, document verification, and underwriting from messy financial documents — using AI to extract fraud-checked data and localized risk signals that power faster, better credit decisions.

Under the hood, Kita is a learning engine. We link document-level signals to repayment outcomes, allowing our models to continuously improve fraud detection and risk assessment over time. This creates a compounding advantage for lenders as their distinct underwriting decisions feed back into the system.

We’re Carmel and Rhea. We met before Stanford and have been building together ever since. Carmel is from Manila, is a repeat founder, and spent three years in product at Apple. Rhea has a research background in computer vision and received the highest honor in Stanford Computer Science. Together, we combine deep local context with strong technical execution to build the infrastructure that expands access to credit in emerging markets.

Full teardown

No full teardown yet. On the deep list.

Technical detail
Slug
kita
Lens hash
179096c479
Pass
screen
Stale
no