How Silk River Capital Got Fundraise-Ready in Two Weeks with Bridges

2 weeks
model delivered
Dual-capital
equity + debt structured separately
85%
advance rate on credit facility

Tim and his team didn't just build a model — they built the capital strategy behind it. We came in with a thesis and left with a defensible plan every serious investor could stress-test.

John Preuninger, Founder & CEO, Silk River Capital

Challenge

Pre-Revenue, No Loan Book — and Needing to Raise Both Equity and Debt at the Same Time

John Preuninger is a serial founder. He co-founded Amber Road, took it public on the NYSE, and sold it to E2open for $425 million in 2019. For his next company — Silk River Capital, a digital lender for small and mid-sized businesses in the U.S. infrastructure sector — he needed to raise capital before writing a single loan.

That meant going to investors with no revenue, no originations, and no loan book to point to. Every assumption in the model — time to first loan, customer acquisition cost, headcount ramp, default rates — had to come from first principles and industry benchmarks instead of Silk River's own data.

The harder problem was that Silk River needed two completely different types of capital at once: equity to hire the team and build the product, and a debt facility to actually fund the loans it would originate. Equity investors and debt providers ask entirely different questions. A model that tried to tell both stories in one place would answer neither. John needed someone who understood lending economics from the inside — not just how to build a spreadsheet.

"Every number had to come from scratch. We needed a model that could hold up in a room full of credit investors asking one set of questions and equity investors asking a completely different set — at the same time."


Solution

Building a Model That De-Risks the Business for Both Equity and Debt Investors

John engaged Tim Salikhov, CEO of Bridges, specifically for his lending operating experience — including time at Kabbage, where he worked directly with small business credit economics — and his command of unit economics in capital-intensive models. The engagement moved fast.

A Burn Discipline Framework Built Before Any Growth Assumption

Tim started by establishing the capital constraint before touching growth inputs — so every downstream assumption had to earn its place.

  • Built a bottoms-up MVP team cost with zero revenue assumed
  • Anchored burn to a 30-month runway rather than the standard 18, creating real discipline
  • Set a hard monthly burn cap that every hiring and spend assumption had to fit inside

That constraint became the spine of the financial model — not a guardrail added at the end, but the organizing principle everything else was built around. It gave the equity story a credible foundation before a single growth assumption was made.

Separate Operating and Credit Models, Interlocked but Clean

With the burn framework set, Tim built two distinct models — one for the operating business, one for the lending engine — each with its own logic and its own audience.

  • Modeled customer acquisition and headcount growth bottom-up on the operating side
  • Modeled origination volume, net interest margin, and loss rates independently on the credit side
  • Added base, upside, and downside scenarios to both, so investors could stress-test either without contaminating the other

That separation made each story self-contained. Equity investors could evaluate burn, hiring, and path to PMF without wading through credit assumptions. Debt providers could evaluate facility sizing and loss economics without getting lost in headcount sequencing.

Scenario Architecture Designed to Minimize Dilution and Optimize Terms

With both models running, Tim translated the underlying assumptions into the specific terms each capital source actually evaluates — and engineered the scenarios to protect the founders.

  • Packaged equity outputs around capital efficiency, milestone logic, and Series A readiness signals
  • Packaged credit outputs around facility sizing, coverage ratios, and loss-rate economics
  • Built dynamic scenario modeling so the team could show exactly how much to raise, at what valuation, alongside what size debt facility — and why

The result wasn't just a defensible raise target. It was a live negotiating tool — one that let John walk into both conversations knowing which scenarios protected dilution and which ones gave away the most.

"What set this apart was the lending background. Tim understood infrastructure credit economics from the inside, not from a textbook. The model reflected how this business actually works — not how a generic fintech model is supposed to look."


Results

Silk River Goes to Market Fundraise-Ready in Two Weeks

In two weeks, Silk River went from a thesis and a blank model to a fully defensible capital plan — ready to walk into both an equity raise and a debt facility conversation.

  • Two capital stories, one model — equity and credit assumptions are fully interlocked but cleanly separated, so neither conversation can contradict the other
  • Infrastructure-specific credit economics — loss rates, margin assumptions, and reserve logic reflect the vertical, not generic fintech benchmarks
  • Dynamic scenario modeling — the team can move any input and immediately see how the raise size, dilution, and debt facility size respond

The model gives Silk River what pre-revenue companies almost never have going into a raise: a defensible, re-derivable capital plan that sophisticated investors on both sides of the table can stress-test without finding a seam.

"We came in pre-revenue with a thesis and a team. We left with a capital plan that tells the right story to equity investors and credit investors — without either one contradicting the other. That's what we needed to raise on our terms."