The most valuable data cannot be labeled in time to matter.

01 · Labels

Machine learning needs homework

Humans must name attacks, tumors, and brain signals before software can act.

02 · Cliff

The moments that matter have no key

Zero-days, overnight neural drift, quantum answers past classical check, silent GPU faults.

03 · Cost

Buyers already pay for the failure

Failed GPU clusters. Bad Quantum shots. Lost data and lawsuits from network attacks. Billions in lost revenue, opportunity, and stalled technology progress from systems that humans can't trust.

04 · Gap

Nothing measures fidelity today

Anomaly scores guess. Supervised stacks wait for labels. Exhaustive check ends past ~50 qubits.

A label is a record of hindsight. High-stakes decisions are questions about right now.

VERITY isn’t built to look for bad or malicious data. It measures what NORMAL data looks like, and detects deviations from the norm.

Calibrates in seconds on unlabeled data flows, scores every new output, returns an auditable posture, and refuses to certify the data when it detects deviations from the baseline.

No answer key required

Calibrates to what “normal” looks like from the live system, not from a catalog of past attacks or labeled examples.

Works offline

CPU-only. Air-gap capable. Runs inside water plants, power stations, and classified networks where data never leaves.

Says REFUSE

Regulated buyers need a system that can decline. Every verdict is auditable after the fact.

One engine, many industries

Same method across quantum, network security, and brain interfaces. Swap the domain surface, keep the instrument.

Old software asks “which label is this?” VERITY asks “is this still faithful?”

As generation becomes abundant, verification becomes scarce. That scarcity is where the money is.

Catch what no one has labeled yet, inside the building.

Offline attack detection for water, power, and classified OT, where data can never leave.

No attack labels. “Normal” comes from the live baseline.

No GPU. No cloud. No connection.

Routes uncertainty instead of flooding operators.

Catch the threat you’ve never named, without shipping your plant to the cloud.

VERITY calibrates to what “normal” looks like on site, flags dangerous departure, and refuses to pretend when evidence is thin. Built for water, power, and classified OT.

Vs. failure cost: the average breach now costs $4.99M and the tail runs to Equifax scale, and novel AI attacks never repeat a signature. The buyer isn’t buying another IDS pack. They’re buying “this is not normal” before anyone labels the attack.

Wake up and use it. No morning recalibration.

#1 on the public FALCON H1 leaderboard as of Oct. 29, 2026. Held-out R² 0.71, ahead of the NDT2 Multi Oracle baseline at 0.63. That is the shift from experiment to product.

Calibrates from the first two seconds of unlabeled activity.

Sub-megabyte decoder, millisecond CPU runtime.

Neural data stays local. No cloud GPU in the loop.

Wake up and move, without a specialist rewriting yesterday’s labels.

VERITY calibrates from a few seconds of unlabeled neural activity, so an implant becomes a product used at home, not a lab demo that needs daily supervision. Wake up and use it: no morning recalibration ritual. That is the path from clinic experiment to a shelf at Best Buy.

Vs. failure cost: a $50K to $100K implant plus GPU and daily staff stays a clinic demo. The buyer isn’t buying a better decoder of yesterday’s labels. They’re buying an implant that still works after the brain drifts overnight.

VERITY NANO, seizure detection that runs on the wearable itself.

An on-device seizure-detection engine for wearable EEG and body sensors. It needs no cloud, no streaming and no phone in the loop to detect, and it alerts in real time.

How it works

Calibrates to each patient’s own normal

It calibrates to each patient’s own normal, recognizes seizures seen across other patients, and alarms only when the evidence agrees. When a sensor drops out, it reports that it can’t measure rather than guessing.

Tiny

Fits the smallest wearable chips

About 43,000 operations per second, under 1 KB of per-patient settings, and low-bit integer math. That fits the smallest wearable chips, and the radio stays off until there’s an alarm, which is what makes long battery life possible.

Clinician-tunable

The care team sets each patient’s tolerance

The device produces the full sensitivity and false-alarm curve. The care team sets each patient’s tolerance from the phone app, and it can be updated as the patient changes.

Results so far on SeizeIT2, a public multi-center wearable dataset.

Development results. Independent sealed confirmation is underway.

The ask: We’re looking for wearable hardware partners on a 30-day-wear device with real-time on-device detection.

Should I trust this quantum result?

VERITY graded a 156-qubit IBM processor from a Mac Mini. No classical supercomputer required.

See strong vs weak hardware before you spend the job.

Characterize on a fraction of the shots.

Refuse when the evidence isn’t there.

Stop paying for quantum answers you cannot trust.

VERITY tells a lab, vendor, or defense buyer whether a quantum job is worth believing, before the next budget cycle burns on it.

Vs. failure cost: stop burning 1,024 to 8,192 shots at ~$96/min on faith. The buyer isn’t buying “better qubits.” They’re buying a clear go / no-go on every job.

What happens when verification fails?

Doesn’t catalog what bad looks like. Measures what normal looks like. Failure is expensive. The instrument runs where the failure happens.

Infrastructure economics: tiny runtime, huge value-to-price.

Near-zero marginal cost per deployment plus large value-to-price headroom is the financial signature of infrastructure, not services.

A new field of measurement, patent-pending protection, and cross-domain proof.

VERITY’s VSEL security architecture is the shell VERITY runs inside.

What VERITY’s VSEL security architecture provides:

Two Founders. Multiple Cross-Domain Proofs. One Instrument.

Marty Oelrich, MACo-Founder, Chief Scientist

Inventor of the core data fidelity method. Forensic credibility assessment first: 5,000+ high-stakes examinations, zero subpoenas, zero complaints. Then twelve years running Saw & Steel, his sign manufacturing company, at 4.99 stars across 2,500+ reviews. He owns the science and its reproducibility.

Credibility measured, produced, now instrumented.

Tony MangnallCo-Founder & CEO

Launched the hit TV show Poker Night In America on CBS Sports Network and sold it to Rush Street Interactive after 14 seasons. An autodidactic systems builder who can inspire small teams to tackle big jobs. He independently reproduces the work and runs formal red-team review, while driving outreach and building the investor coalition.

Built a category-leading property, sold it, doing it again.

Dorman BazzellBoard of Directors

North Dakota’s first Chief Data Officer, leading the state’s enterprise information management and software development programs from 2018 to 2021. Now Chief AI Officer at BISBLOX, a venture studio in Mandan, North Dakota. Before public service, more than 30 years in the private sector, including analytics practice leadership at Capgemini and Hitachi Consulting and CIO of Coin Acceptors.

Newest member of the Credasis Board of Directors.

Two Founders, Self-Funded, Based in Phoenix and Fargo.

Raising $5M pre-seed to turn proofs into paying logos.

Why now: each milestone re-rates the company from IP option to strategic asset. Financing buys execution, not more invention of the instrument.