Problem

Complexity Tax

Manual quotes let lenders price-discriminate

• Lead sites sell your data to the highest bidder - not the lowest quotes
• Brokers take 1-2% in cash or hidden in fees. Manual, slow
• Lenders profit from confusion - buyers can't compare "apples to apples"

Result: $126K overpaid on a $700K 30-year loan

Solution

Your private AI mortgage shopper

• It calls, emails, and submits forms to lenders for you from private lines
• Converts messy quotes into comparable, verified offers
• You stay anonymous until you choose who to lock with

Saving buyers five figures

Market

$1.8T U.S. mortgages, 4M homes yearly

$180B overpaid annually / ~ $45K per buyer in rates and fees

• 10% of buyers (≈500K at $400 each) = $200M annual revenue
• 5% of U.S. real-estate brokerages × $1K/mo = ~$63 M ARR

Expansion worldwide and verticals:

U.S. Auto loan ≈ $1.5T - similar quote complexity, similar AI agents

Competition

Everyone sells to lenders - we work for buyers

• Rate sites sell leads (LendingTree, Bankrate): teaser rates, hidden fees, spam
• Brokers: 1–2% in cash or hidden in fees. Conflict of interests
• Emerging AI quote tools (Approval AI - YC S25) paid by lenders

Selectic.ai: buyer-only flat fee, no conflicts

Business Model

Flat-fee consumer SaaS, not a broker

• Scout $300 | Hunter $400 | Closer $800
• No broker licensing
• Unrestricted marketing channels untouchable by lenders or brokers

Later: B2B via real estate brokers - $1K/mo embedded quote shopping

Traction

58 pilot customers

• Avg. ticket: ~$400
• AI API costs: $70 (30 lenders @ ~$2.35 each)
• Gross margin: 82.5%
• CAC: $18

Launched high-intent Google Search ads - paused until full rollout

Team

Founders who lived the problem

Married co-founders experienced in technology and regulated U.S. markets

Ask

$1M Pre-Seed (SAFE)

Use of Funds: AI accuracy, user acquisition, and reserve

Milestones:

• 10K paying users
• Expand into the B2B channel

Thank you!