Slide 2: Pain

Complexity Tax

Opacity = margin. Manual quotes let sellers price-discriminate and pad fees

• Points, credits, junk fees reshuffle price across lenders
• Lock rules and timing change the true total cost you'll pay
• Fragmented channels (screenshots, PDFs, verbal quotes) block comparison
• Result: buyers give up to "good enough," paying thousands more

Slide 3: Solution

Verified Savings

• Agent does the legwork (calls, emails, follow-ups) so you don't
• Standardizes everything lenders vary: points / fees / lock rules
• Ranks offers by dollars saved over your horizon, not APR alone
• Documented terms to support re-quotes, float-downs, and closing

Slide 4

Why Now

• Agentic AI now handles messy multi-party workflows (calls, emails, docs)
• Rate volatility makes apples-to-apples comparison urgent
• Consumer-paid, privacy-first beats lead-sell marketplaces
• Lenders face volume pressure and compete when outreach is organized

Slide 5: Competitors

They Work for Lenders

• LendingTree, Bankrate, NerdWallet: sell your data to lenders
• Rocket Mortgage, Better.com: push their own rates
• Zillow, Redfin: monetize through lender referrals and captive lending
• Blend, Roostify: lender-side software
• We work for you: consumer-paid, no kickbacks, no lead selling

Slide 6: Size

Two Markets, One Platform

• Mortgage originations (2025): ≈ $1.85T
• Real-estate commissions (historical): ≈ $100B per year
• Mortgage Shopping Agent: lowest total cost
• Real-Estate Agent: negotiation and deal control
• Synergy: align rate-lock windows with offer timelines → better mortgage rate + better purchase price

Slide 7

Business Model & Compliance

• Revenue: Flat fee per shopping sprint (paid by the borrower)
• Subscriptions: Borrower (re-quotes / refi monitoring); Broker/Team (software to run sprints)
• Not a broker: We don't take applications, offer credit, lock rates, or accept lender money — no broker license needed
• Referral rules: No lead selling, no referral fees, no "things of value" — RESPA §8 anti-kickback isn't triggered

Slide 8

Early Proof and Metrics

• Paying customers: 65
• Average price: $400
• Lenders contacted per client: 30
• Quote response rate: 75%
• Average savings vs first quote: 0.45% → $40k
• AI API costs: $35 (30 lenders @ ~$1.17 each)
• Gross margin: 91% ($365 per customer)
• Customer acquisition cost: $18 (paid ads)
• Contribution margin: 87% (LTV:CAC ratio of 19:1)

Slide 9

Grow

• Direct to consumer: High-intent search ads (Google, Microsoft)
• Flow: Savings estimator → short intake → paid shopping sprint
• Output: Lock-ready, normalized offers — "one form, one day, verified savings"
• Next funnel (brokers/teams): Outbound with the same agent tech to run sprints for their clients; sold as a subscription

Slide 10

Product Roadmap

• Outreach agents: Automated lender contact (calls, emails, follow-ups)
• Negotiation co-pilot: Counter-offers, lock / float-down / extension math
• Agents for teams: Run shopping sprints for broker clients; white-label reports
• Next Agent (real estate): Buyer-agent copilot — negotiation, comps, showings, offer packaging, deal control

Slide 12

The Ask and Plan

• Raising: $1M
• Scale: Full-cycle workflow (intake → outreach → normalization → negotiation → lock-ready)
• Extend: Roll out real estate co-pilot
• Grow: Scale high-intent search
• 12-month goals: $50M+ ARR