Quadfence Corp. · Sugar Land, Texas · Pre-product
A verdict, and the arithmetic behind it.
In December 2022 our founder bought a dental practice. Her accountant went through the books. Her broker handed her a page of census data: education levels, a gender split, a race breakdown.
Nobody could tell her how many dentists were already fighting over the same patients, or whether the neighbourhood turned over faster than she'd ever keep up with. She signed anyway. Most dentists do.
AiRadics is the tool she needed and is now building. It tells a dentist whether a market can be won. Then, if they want it to, the platform goes and wins that market for them — and for nobody else in their territory.
Quadfence is the company underneath it. We build AI for decisions where being wrong is expensive, which means a recommendation is no use unless you can check it, see where it came from, and get the same answer twice. Dental is where we prove that. It is not where it ends.
178,000
US dental practices, mostly independent
under 5%
Largest share held by any operator in the dentists industry (IBISWorld)
4.3%
Of practices needed for a $1B outcome
What AiRadics is
An analyst and a production line, in one system.
Three things, and putting them in one place is the point.
It reads the market
How many dentists per capita already compete for the same patients. How fast the households nearby turn over. What the payer mix on the ground actually is, and which clinical services the competition has left alone. A CPA can audit the books. None of this is in them.
It reads the money
Every channel reports in. The model works out what each one actually produces, what a patient costs through each of them, and where the next dollar earns most — then the budget moves. Not five numbers on a dashboard. An answer.
It makes the work
The website, the landing pages, the ads, the images, the video — all generated, and none of it live until it has cleared the governance gate: FTC rules, ADA guidance, the state dental board, and Google’s stricter standard for health content. No change orders, because producing an asset costs us a fraction of what it costs an agency to have a person make one.
An agency has people who can make the work but cannot honestly measure it. An analytics tool can measure but cannot make anything. In one system the analysis decides what to make — and making it is nearly free.
Why this team
One of us is the customer. The other has shipped governed AI inside a bank.
Dr. Soujanya Maddipati — Founder & CEO
DDS, Univ. of Colorado Denver · MPH, Univ. of Oklahoma
She has run Mi Smile Family Dental in North Houston since she bought it at the end of 2022. Medicaid, CHIP, Medicare Advantage, PPO. She still sees every patient herself. Then came three years of paying agencies she could not hold to a number, any of whom could have signed the practice a mile away the following week.
Dentists buy from dentists. That is not a marketing line, it is how the profession works, and you cannot hire it.
Chaitanya Maddipati — Co-founder & CTO
20 years, data & AI platforms in regulated industries
Executive Director and Principal Engineer at Wells Fargo over the bank’s customer data platform: forty engineers, a $15M portfolio, 900TB onto BigQuery. He ran the bank’s first application onto Google Cloud and wrote the reference architecture the rest of it built against. Before that, Publicis Sapient across UnitedHealth Group and TikTok, and the data behind US credit-card acquisition at Capital One.
The hard part here is not generating marketing. It is generating it where almost nothing can be published unchecked and a regulator can ask why. Compliance runs before generation, not as a review afterwards.
Neither half works alone. An agency with better software still cannot get a dentist to trust it, and a dentist with a good idea cannot ship a governed multi-model engine.
The pilot
One clinic, chosen because it is the hard case.
AiRadics is being built against a live general practice — our founder’s own. It is the reference implementation, not a demo. Every module ships against real channel data, a real payer mix and a real patient book before it is offered to anyone else.
A pilot only matters if what is learned there transfers. Most single-clinic pilots do not, because most clinics are narrow. This one runs four payer classes, a mixed catchment and a full service line at once — so the axioms it produces generalise to the next practice instead of having to be relearned.
Twenty shallow clinics would produce twenty thin datasets. One clinic exercising every payer class produces an ontology the twenty-first can actually use.
The market
A $1B outcome needs 4.3% of one fragmented vertical.
Each number below is a count of practices multiplied by what one pays us in a year. We haven't borrowed anything from a bigger adjacent market to make it look larger.
$2.88Bgross market
178,000 US practices at an indicative $16,200 annual contract value. Recurring fee only — media runs on the practice’s own accounts and is excluded.
$1.87Bserviceable
Independent practices only. We assume 65% remain independent, and affiliation is reported at 13–16% today. We have deliberately left small and mid-size DSOs out of this number even though they are buyers too, which means consolidation is less of a risk here than the figure implies.
4.3%share required
7,716 practices at the same indicative figure is $125M ARR, which is roughly a $1B company at an 8× multiple. We would be the largest player in this niche and still hold four percent of it.
We don't have to win this market, only a slice of it. The three largest dental marketing agencies we can put a number to serve roughly 9,100 practices between them, which is 5.1% of the market. The leader has 4.2% after twenty-three years and private-equity backing. Sizes and sources are set out below. The engine itself doesn't care that the customer is a dentist, which is why small medical practices are the obvious second move. Same shape of problem, different vocabulary.
Every figure on this page is sourced, dated and set out with its limits — including where our own assumptions differ from the published comparables. See the market evidence →
The round
We are not raising to find out whether this works. We are raising to go faster.
The slow, uncertain part is building an ontology and a governed engine against a real practice with a real payer mix. That is in progress. What money buys is the part that is purely capacity: finishing the product, and putting clinics onto it.
A new practice is provisioned from the same blueprint every time rather than built — which is what makes a one-day onboarding possible and an agent-led sale viable. Pricing sits in line with what a practice already pays an agency for two channels and nothing else, and includes considerably more.
No practice outside our own is running on this yet, and we will not pretend otherwise. What exists is the pilot, and the ontology it produces. That is the asset this round is built on — not a slide, and not twenty shallow trials.
Get in touch
If you run a practice, or you want the deck.
We are pre-product and looking for a small number of Texas practices to work with once there is something to work with. Investors: the deck and the operating model are available on request.