Seed Round Presentation · Brian Brebitzke, Founder

Trust
Infra
structure

The definitive safety layer for high-stakes AI deployment — powered by the Epoche v5.0 Framework.

MODEL-AGNOSTIC EPOCHE v5.0 ENTERPRISE-READY SEED ROUND
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The Problem

Current AI Safety
Is Fundamentally Broken

01
Brittle Binary Logic

Traditional guardrails treat generative outputs as binary: completely right or wrong. The real world is never that clean.

02
Silent Hallucinations

Subtle, deeply-logical errors slip through undetected — creating severe enterprise liability in regulated industries.

03
Alert Fatigue

Patching gaps with basic filters floods operators with low-fidelity warnings, causing them to mute safety overrides entirely.

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The Solution

Introducing Epoche

[W]
Model-Agnostic Wrapper An external software layer sitting seamlessly around any foundational LLM — OpenAI, Anthropic, or open source.
[R]
Operational Risk Estimation Stops chasing the impossible goal of "eliminating mistakes." Focuses on continuous, mathematical risk management instead.
[U]
The "Unknown" State Maps uncertainty into a distinct third state — withholding judgment rather than forcing an overconfident hallucinated guess.
EPOCHE
CONFIDENCE
ENTROPY
AGREEMENT
CONTRA-
DICTION
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Deep Tech Innovation

Dependency-Aware
Signal Modeling

Covariance Matrix — Ledoit-Wolf Shrinkage
CONF
AGREE
ENTPY
CONTRA
1.00
0.61
−0.42
−0.38
0.61
1.00
−0.37
−0.29
−0.42
−0.37
1.00
0.58
−0.38
−0.29
0.58
1.00

Tracking 4 indicators as a unified system catches correlated signal collapse that independent analysis will always miss.

Confidence Inflation Detection

Traditional tools analyze metrics independently, missing systemic failures when multiple indicators blindly echo each other.

Covariance Estimation

Epoche tracks Confidence, Agreement, Entropy, and Contradiction as a unified matrix using Ledoit-Wolf shrinkage for precision.

Signal Collapse Detection

Flags an alert the exact millisecond independent validation streams begin suffering from correlated collapse.

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Product UX

Graduated Friction Policy

1
Transparency Prompt Subtle contextual cues embedded in output. Low friction for low-uncertainty interactions. User flow uninterrupted.
2
Soft Intervention Visible uncertainty flagging with contextual explanation. Operator alerted with decision support data.
3
Mandatory Confirmation Hard stop requiring explicit expert sign-off. Reserved for high-stakes outputs with elevated covariance collapse risk.
FATIGUE GUARD: If a user dismisses >30% of interventions, Epoche auto-recalibrates to preserve workflow integrity.
Epoche Runtime Layer
"The recommended dosage for adults in this clinical context is 40–60mg/day, adjusted by renal function parameters..."
⚠ L2 Covariance anomaly detected. Confidence and Agreement indicators showing correlated deviation. Expert review recommended before deployment.
UNCERTAINTY
DYNAMIC
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Empirical Validation

v5.0 Benchmark Results

Dataset Precision Recall F1 Score AUC-ROC ECE
TruthfulQA (MC) 0.81 0.76
0.78
0.84 0.043
HaluEval (QA) 0.79 0.82
0.80
0.86 0.051
FActScoreBio 0.77 0.80
0.78
0.83 0.048
Baseline Threshold — —
0.61
0.71 —
+28% F1 · +21% AUC-ROC OVER BASELINE
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Commercial Strategy

Built for Enterprise Scale

⚡
Capital-Efficient SaaS

Kermati skips the multi-million dollar expense of training baseline LLMs — delivering maximum value at minimum cost structure.

🔓
Zero Infrastructure Lock-in

Enterprise clients freely swap underlying models — OpenAI, Anthropic, or open source — as the technology evolves beneath them.

🔒
Sticky Governance Layer

While models shift, compliance infrastructure, audit logs, and security controls remain anchored by Kermati. Durable, recurring value.

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The Founder

First-Principles Engineering

BB
Brian Brebitzke
Founder & Architect · KERMATI
Strict logical, first-principles approach to systemic risk management — stepping outside the echo chambers of conventional software dogma.
Architected the framework focused on quantifying uncertainty rather than chasing binary absolutes that the enterprise market couldn't deliver on.
Main objective: moving the fully-specified Epoche v5.0 mathematical pipeline into a hardened, production-ready enterprise engine.
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Execution Roadmap

6-Month Sprint to Market

Month 1–2
Core Engineering

80% of seed capital directed to recruiting specialized ML engineers and advanced statisticians.

Month 3–4
Runtime Hardening

Transitioning v5.0 framework into an optimized production engine. Stabilizing API response latency.

Month 5
CUSUM Drift

Deploying real-time sequential drift monitoring to protect against longitudinal model updates.

Month 6
Live Pilots

Beta integrations with early-access enterprise partners in Finance and Life Sciences verticals.

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Use of Funds

Seed Round Allocation

Total Raise
$[ 2M ]
← FILL IN YOUR RAISE AMOUNT
Engineering & Talent [ 30% ]
ML engineers & statisticians (per roadmap Month 1–2)
Infrastructure & Dev [ 30% ]
Production hardening, API latency optimization
Enterprise Pilots [ 10% ]
Finance & Life Sciences beta integrations
Operations & Legal [ 20% ]
Compliance, IP protection, business operations
What This Funding Achieves
1
Production-Ready Epoche Engine
v5.0 framework hardened into a deployable enterprise API within 6 months.
2
[ XX ] Signed Pilot Partners
Live integrations in Finance and Life Sciences — LOIs or signed agreements. ← FILL IN TARGET
3
Series A Positioned
Runway and traction metrics to support a Series A raise at [ XX ] months post-seed. ← FILL IN TIMELINE
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Join The
Seed Round

We're building the definitive trust infrastructure for critical AI systems. Help us harden Epoche into the production engine the enterprise world demands.

Email
Brebitzke@kermati.com
Phone
(530) 559-0491
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