Corlen: AI-native intake and guideline checks for commercial real-estate lending

Corlen is an AI-native loan-origination platform for commercial real-estate lenders and brokers. The buyer decision is whether a lending team wants intake, document checks, follow-up, and guideline enforcement in one deal record—while the underwriter keeps the final call.

What it does

Corlen says it unifies applications, messages, documents, and status around one loan record; reads each file against lender guidelines; flags missing or stale materials; and sends scheduled follow-ups. Its platform sits alongside an existing LOS and POS, with configurable rules, source-linked audit logs, and borrower or lender permissions (Corlen homepage; Speedrun profile).

Fact	What the public sources say
Buyer	Commercial real-estate lenders, brokers, and private-credit teams
Workflow	Application intake, document verification, guideline checks, follow-up, and file packaging
Public product claims	The homepage says 90% less manual document chasing, under five minutes to review a package, and ten minutes to go live on guidelines
Human boundary	Corlen says AI prepares the file while the underwriter makes the final call
Founders	Waruna Yapa and Meheresh Yeditha

Why it fits

The practical advantage is earlier certainty. A broker can package a deal once, see what a lender is missing before submission, and keep every conversation and document tied to the record. A lender can apply the same checklist across branches and reviewers instead of discovering gaps through a late conditions list.

The speed figures are company claims, not an independent lending-operations study (Corlen homepage). A buyer should test incomplete packages, changing guidelines, multiple lender programs, stale documents, borrower follow-up, and the exact write-back to the existing LOS. Security statements on the homepage—encrypted storage, role-based access, tenant separation, and audit logs—are company-published; procurement should request the underlying controls. Pricing was not published.

Yapa says he founded a real-estate investment firm and closed 25 deals after working at Meta, LinkedIn, and Microsoft; Yeditha previously led AI and infrastructure at Rippling (Corlen homepage). That combination fits the workflow's mix of real-estate judgment and enterprise systems.

Short version: Corlen is a strong candidate for lenders whose bottleneck is incomplete files and follow-up, not underwriting judgment. Start with one guideline set and measure time to a decision-ready package.

Sources checked — 2026-09-19

• Speedrun company profile
• Corlen homepage