OMNIA
The Behavioral Intelligence Layer for SMB Lending
SMB Lenders Compete for the Same Stale Leads.
By the time a small business submits an application, it's already been sold to 10+ funders. ISOs, lead aggregators, and UCC lists recycle the same merchants until margins collapse. The real value is identifying SMBs actively seeking capital — before they apply.
$1.4T
SMB Credit Gap
in unmet U.S. funding demand
59%
of SMBs
actively seeking capital
10+
Funders Bid
on every aggregator lead
Lead Sources vs. OMNIA
UCC Lists
RecycledPublic filings sold to every funder. Saturated on day one.
Lead Aggregators
SharedSame merchant submitted to 10+ funders simultaneously.
ISO Networks
BrokeredBroker-controlled deals with thin margins and no exclusivity.
PPC & Paid Search
ReactiveSkyrocketing CPCs. Bottom-of-funnel only. No early signal.
87%
AccuracyPre-Application Intent Detection
Identifies SMBs exhibiting capital-seeking behavior 30–90 days before they apply anywhere. Delivered exclusively — never to another lender.
30–90d
Signal Window
85%
Noise Reduced
Live
Processing
OMNIA is the Intelligence Layer for SMB Lending
We sit between raw web behavior and a funder's underwriting desk — modeling which small businesses are actively seeking capital before any application, UCC filing, or aggregator submission ever happens.
A Data Moat That Compounds Over Time
Proprietary SMB Data
Owned first-party behavioral signals across millions of small businesses: capital-seeking searches, funding site visits, application abandons, and cash-flow stress patterns.
Business Identity Graph
Stitches business entity, owner, EIN, domain, and device into a single resolved profile — so intent maps to a fundable merchant, not an anonymous click.
Funded-Deal Feedback Loop
Every funded deal feeds back into the model. Scoring sharpens with every closed file, compounding accuracy our competitors can't replicate.
A Living Knowledge Graph
Every funded deal outcome — behavioral signals, application data, financial profiles, partner feedback, and funded or unfunded results — is plotted onto a vectorized database. A continuously expanding graph of what a closeable file actually looks like.
The graph surfaces correlations no human analyst could find at scale: which signals preceded funding, which profiles predict rejection, which combinations map most reliably to closed revenue. Every new deal sharpens every future prediction.
Not a static dataset — a living, self-improving intelligence structure. A competitor starting today would need years of equivalent funded volume to build a comparable graph.
Behavioral Signals → Funded Deals
Funding Intent Trajectories
Track how an SMB's capital need builds over days and weeks — from research to active shopping.
Behavior-Based Pre-Screening
Score on observed buying behavior + verified credit and revenue, not just demographics or UCC age.
Real-Time Funding Alerts
Notify the lender the moment an SMB crosses the threshold from research into active capital-seeking.
Exclusive File Delivery
Each pre-screened merchant goes to one lender. No aggregator dilution. No bidding war.
Feedback Loop Refinement
Our internal model feeds live funded-deal outcomes from partner lenders back into the algorithm in real time — separating noise from genuine SMB capital intent.
Ingests live funding outcomes (funded, declined, pending) from partner lenders
Reweights behavioral patterns based on what actually converts to funded deals
Reduces raw intent pool by up to 85% to surface only fundable, capital-ready SMBs
BizBee Funding — Omnia's Owned Acquisition Engine.
Omnia doesn't wait for lenders to send files. It owns the top of the funnel entirely through BizBee Funding — a proprietary business lending marketplace at bizbeefunding.com that serves as both the primary deal flow engine and the real-world R&D environment for the Omnia intelligence system.
Every business owner who applies through BizBee generates a labeled data point — behavioral signals, application data, financial profile, and ultimately a funded or unfunded outcome. This is how Omnia's dataset gets built. This is how the algorithm gets trained. This is what makes the intelligence layer proprietary and impossible to replicate without equivalent volume.
BizBee owns the top of funnel. Omnia's email infrastructure drives intent-verified, ICP-matched traffic directly to BizBee. Applicants are processed through the screening engine and matched to lending partners. Omnia controls the pipeline from signal to delivery — end to end.
Every application that runs through BizBee — funded or not — contributes to a proprietary outcome-labeled dataset. Behavioral patterns that preceded good files. Financial profiles that preceded bad ones. Funded deal signals from lending partners. This is the training data that makes the Omnia algorithm more accurate with every cycle.
BizBee is being built as a valuable asset in its own right. Every click, every application, and every funded deal builds domain authority, SEO footprint, and a track record. BizBee has optionality — it can operate as a marketplace, convert to a licensed brokerage capturing 100% of deal economics, or be valued and sold independently. The investment builds two assets simultaneously.
BizBee is not a marketing tool. It is the infrastructure that makes Omnia's intelligence layer real — generating the deal flow, building the dataset, and proving the thesis one funded deal at a time.
This isn't theory. We've run this playbook before.
After spending tens of thousands generating leads through traditional channels — Facebook, Meta, paid social — the unit economics told us everything we needed to know.
Average CPC on social: $6–8. Cost per lead: $25–50. Cost per application: $100–150. Cost per "qualified" application — one that meets minimum requirements on paper: $250–300.
WHERE THE MARKET BREAKS
And here's the problem that number doesn't solve: even at $250–300 per qualified lead, lenders still close less than 5%. Why? Because "qualified on paper" doesn't survive underwriting. Revenue doesn't match stated amounts when verified. Debt service ratios are too high. Existing loan stacks disqualify the file.
The paper qualification and the funded deal are two different things — and nobody in the market has closed that gap.
Omnia does.
By starting with proprietary behavioral intent data — ICP-matched businesses exhibiting active capital-seeking behavior — and reaching them through owned email infrastructure at scale, we drop the cost structure dramatically:
COST PER CLICK
$0.30 – $0.50
conservative vs. $6–8 industry
92%+ lower
COST PER LEAD
Low single digits
vs. $25–50
Step-change
COST PER APPLICATION
$10–20
vs. $100–150
10x delta
COST PER QUALIFIED APPLICATION
$30–50
vs. $250–300
6x delta
That same intent data feeds directly back into social platform algorithms — so when we do run paid campaigns, we're targeting with behavioral intent signals instead of Facebook's generic interest-based algorithm. Lower CPC. Better conversion. Same infrastructure advantage.
This scales linearly. At 2M sends per month the economics work. At 5M, 10M, 20M+ they compound. The infrastructure is self-learning and self-healing — it optimizes without manual intervention.
We've run this model in other industries. The cost structure is proven. What we're validating now with two active lender pilots — partners with $500M+ in combined funded volume — is the close rate lift, and based on the quality of files we're delivering vs. what lenders are used to buying, we're targeting a 3–5x improvement on the industry's 3–5% baseline.
That lift — from 5% to 10–25% — is where the ROI story for lending partners becomes undeniable. And it's where the data moat becomes impossible to replicate.
ROI INFLECTION
CLOSE RATE
3–5x
targeted close-rate improvement on the industry's baseline.
Three-Phase Productization
Exclusive Lender Partnerships
Direct-to-lender file delivery on a revenue-share model. Pre-screened SMB funding files delivered exclusively to one funder per file. Live and generating revenue today.
Pre-Screen API for Lenders & ISOs
Funders, ISOs, and capital marketplaces plug directly into the OMNIA scoring engine to validate intent, credit, and revenue before underwriting touches a file.
Brokerage Model
BizBee becomes a licensed brokerage, capturing 100% of deal economics on every funded deal instead of the current revenue share structure. This path requires licensing and regulatory groundwork but is a natural evolution of the marketplace asset already being built.
Data Model
The proprietary behavioral and outcome dataset — accumulated across tens of thousands of funded deals — becomes licensable to non-competing verticals. Equipment leasing, commercial insurance, corporate credit — any high-ticket B2B market where early intent signal determines profit. The intelligence layer that powers BizBee gets deployed as infrastructure for other industries.
Delivering a 3–5× Close Rate For Lending Partners.
Industry-purchased leads close at a 3–5% baseline. Omnia targets a 10–25% close rate on pre-screened, intent-verified files because each file is behavior-verified, ICP-matched, and screened against the partner's exact underwriting criteria before delivery.
Industry Baseline on Purchased Leads
Omnia Target on Pre-Screened Files
Close Rate Lift for Lending Partners
Building the intelligence layer for how SMBs find capital.
SMB lending is a $1.4T market still sourced through public UCC filings, broker networks, and recycled aggregator leads. OMNIA replaces that with proprietary behavioral data — owned, exclusive, and tuned to the moment a small business decides it needs capital. The longer we run, the deeper the moat.
Proprietary Behavioral Data
We generate it. No funder, ISO, or aggregator owns the SMB intent dataset we're building.
Funded-Deal Learning Loop
Every funded merchant sharpens the model. Replication requires our partner lender network.
Time & Coverage Moat
Each month adds millions of behavioral observations across the U.S. SMB universe.
Exclusivity by Design
Each pre-screened file goes to one funder. The product itself is structurally un-commoditizable.
Join the Pre-Seed Round
Omnia is raising a $500K pre-seed round to activate full send volume, lock in the first 10,000 outcome-labeled data points, and turn two signed revenue share agreements into a compounding, high-margin revenue machine.
Pre-Seed Round
$500K
Market Sizing
TAM
$1.4T
U.S. SMB credit gap — total unmet small business funding demand
SAM
$150B
Annual U.S. SMB working capital, MCA, and term loan originations
SOM
$3.2B
Pre-screened, exclusive SMB lead infrastructure for direct funders & ISOs
Use of Funds
40%
Product & Engineering
Scoring engine, lender integrations, and SMB data infrastructure
25%
Behavioral Data Coverage
Expand proprietary SMB intent dataset across U.S. merchant base
20%
Lender Partnerships
Onboard exclusive funder partners and scale rev-share pipeline
15%
Compliance & Operations
CAN-SPAM, lending compliance, legal, and operational overhead
First-Mover in SMB Behavioral Data
No competitor owns a proprietary, first-party behavioral dataset for SMB funding intent at this scale.
Aligned Revenue Model
Revenue-share on funded deals + per-file pricing + SaaS alerts — predictable, scalable, and aligned with lender outcomes.
Capital-Efficient Operators
Lean team with deep lending, real estate, and intent-marketing experience. Existing infrastructure minimizes burn.
Massive SMB Tailwind
Banks have pulled back from SMB lending. Alternative funders need higher-quality, exclusive deal flow more than ever.
Meet the Team
Operators, engineers, and data scientists with deep roots in lending, real estate, and intent-based marketing — building the behavioral intelligence layer for SMB capital.
Red Sherwood
CEO & Co-Founder
Red brings 15 years of oil and gas experience, where he developed a deep understanding of how markets are shaped by reserves, infrastructure, and control. That perspective led him to a core belief: those who control the data ultimately control the market.
Chris Lewis
CTO & Co-Founder
Chris brings over 10 years of real estate experience and more than $100m closed transactions, combining deep industry knowledge with a proven track record. He also has 6+ years building real estate software and data intelligence SaaS products.
Tommy Liantonio
Chief Data Engineer
Tommy serves as Chief Data Engineer, bringing deep expertise in data systems and intent-based marketing. As a founding partner in two technology companies focused on intent-driven online marketing, he has played a key role in building and scaling data infrastructure.