Pre-Seed · 2025

CIX Platform

Clinical Intelligence Xchange

The first federated AI platform built for healthcare.
Train across every hospital. Move zero patient records.

Confidential — 2025

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The Problem

Healthcare AI is Broken
by Its Own Privacy Rules

Every hospital sits on a gold mine of clinical data — but none of it can leave. Traditional AI needs centralized datasets. Healthcare can't provide them. The result: fragmented models trained on tiny samples that fail in production.

97%

of hospital data is siloed
behind firewalls

18mo

average time to deploy
a clinical AI model

$2M+

typical cost per custom
AI model build

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The Solution

Don't Move the Data.
Move the Intelligence.

CIX is a federated learning platform purpose-built for healthcare. AI models train inside each hospital on local data. Only compressed model weights travel to a central server. Patient records never leave. Intelligence grows everywhere.

Hospital A

Trains locally

→

CIX Central

Aggregates weights

←

Hospital B

Trains locally

98.7% bandwidth savings via sparse weight compression

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How It Works

AI That Matches Itself to Physicians

Hospital admins deploy pre-built models or fulfill physician requests — with zero ML expertise. The platform handles everything.

Deploy

Admin picks from 90+ prediction targets or a physician's custom request. One click to train.

Self-Tune

13 adaptive mechanisms automatically optimize for that hospital's data. No configuration needed.

Federate

Models improve across the network. Compressed weights only — zero patient data leaves.

Predict

Physicians get real-time predictions, explainable drivers, care gap alerts, and what-if simulations.

Physicians can also request custom models — choose outcomes they want to predict, and the platform builds and federates them automatically.

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Product

90+ Prediction Targets Across 14 Specialties

Pre-defined clinical outcomes ready to train on any hospital's data. Each includes explainable drivers, care gap detection, and a what-if simulator.

24

Chronic Care

Heart failure, diabetes, CKD, COPD, hepatic disease

18

Operations

Length of stay, readmission, discharge, no-shows

15

Pharmacy

Drug interactions, adverse events, dosing, adherence

12

Acute Risk

Sepsis, AKI, deterioration, ICU transfer

11

Behavioral

Depression, substance use, fall risk, SDOH

10

Population

Risk stratification, care gaps, cost prediction

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Product Status

A Working Prototype.
Tested End-to-End.

The core platform is built and validated on synthetic clinical data (Synthea FHIR R4). The ML engine, desktop app, and federation protocol work end-to-end in simulation.

ML Engine (QuantileModel V7)95%

Desktop Application (Electron)90%

Federation Protocol85%

Clinical Vocabulary (27,505 codes)100%

Backend API & Server70%

EHR Auto-Integration10%

Production Infrastructure15%

Overall: ~60% complete — Functional prototype with proven architecture. Investment accelerates the path from simulation to production.

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Roadmap

From Prototype to Network

Now

Prototype

Working ML engine, desktop app, federation simulation. Tested on synthetic FHIR data. 90+ prediction targets defined.

0 – 6 Months

Cloud & EHR

Deploy backend to production cloud. Build automatic EHR connectors (SMART on FHIR, HL7). First hospital pilot with real clinical data.

6 – 12 Months

Validate & Partner

Clinical validation on real patient outcomes. Partner with 3–5 hospitals. First federated training rounds across live sites.

12 – 18 Months

Grow the Network

Scale to 10+ hospitals. Network effects kick in — every site makes every model better. Launch SaaS subscription model.

Key milestones funded by this round: Production cloud deployment, first EHR integration, first hospital partnership, clinical validation study.

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Technology

What Makes CIX Different

Zero-Configuration AI

Automatic Optimization — The model finds its own optimal learning speed for each hospital's data
Rare Condition Handling — Automatically rebalances for diseases that affect 1 in 20 patients vs. 1 in 2
Smart Early Stopping — Predicts when training will plateau and stops exactly at peak accuracy
Works on Any Data Size — Small rural clinic or large academic center — same platform, same results
Output Auto-Detection — Platform determines whether a target is binary, numeric, or categorical from the data itself

Privacy-First Architecture

Zero Data Movement — Patient records never leave the hospital. Only compressed model weights are transmitted.
Sparse Compression — 98.7% of weight data eliminated — only tokens used at that hospital are shared
Explainable Predictions — Every prediction shows which clinical codes drove the result and why
What-If Simulator — Physicians can ask "What if blood pressure drops 20 mmHg?" and see projected outcomes
Standards-Based — Built on FHIR R4, LOINC, ICD-10, SNOMED CT, and RxNorm — ready for real EHR integration

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Market Opportunity

A $20B+ Market
Waiting for the Right Architecture

$20B+

Healthcare AI TAM by 2030

16.5%

CAGR Federated AI in Healthcare

$141M

FL Healthcare Market by 2034

Every hospital needs AI. None can share data. Federated learning is the only architecture that solves this. CIX is the only complete, healthcare-specific, self-tuning federated platform on the market.

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Business Model

Three Revenue Streams

🏥 SaaS

Hospital Subscriptions

Annual platform license per hospital. Deploy pre-built models, access network intelligence, receive continuous model updates.

🔬 Custom

Model Development

Physician-requested custom predictions. Build once, federate across the network. Revenue per model created.

📊 Data

Aggregated Intelligence

De-identified, aggregated clinical insights for life sciences. Zero PHI. Population-level patterns from network-wide learning.

Network Effect: Every new hospital increases model accuracy for all — creating natural lock-in and compounding value.

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Competitive Landscape

The Only Complete Platform

Capability	CIX Platform	Epic / Cerner	NVIDIA FLARE	Point Solutions
Federated Learning	✓	✕	✓	✕
Pre-built Prediction Library	90+ targets	Limited	✕	1–5 models
Self-Tuning (Zero Config)	13 mechanisms	✕	✕	✕
Explainable Drivers	Per-prediction	Basic	✕	Varies
Custom Model Creation	Physician-driven	✕	Dev required	✕
Healthcare-Specific	Built for it	✓	Generic	✓

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Competitive Moat

Four Compounding Advantages

01

Data Network Effect

Every hospital that joins improves models for all. Late entrants can't replicate network intelligence without the network.
02

27,505-Token Clinical Vocabulary

LOINC + ICD-10 + SNOMED + RxNorm unified into a single learned embedding space. Years of clinical engineering.
03

Self-Tuning Architecture

13 adaptive mechanisms mean zero ML expertise required at the hospital. This isn't a toolkit — it's a turnkey product.
04

Full Clinical Spectrum

90+ prediction targets across 14 specialties. Competitors offer single-disease point solutions. CIX covers the entire hospital.

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Team

Built by Engineers.
Driven by Mission.

Cassidy Draker

Chief Executive Officer

Business strategy, healthcare partnerships, and go-to-market execution.

Ray Noruzi

Co-Founder & CTO

ML architecture, federated systems, and full-stack platform engineering.

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Use of Funds

From Prototype to First Paying Hospitals

Your capital bridges the gap between a working prototype and a production-ready platform with real hospital partners.

Engineering — Cloud Deploy, EHR Connectors, Production Hardening 35%

Clinical Validation — Real Hospital Data, Outcome Studies, Regulatory 30%

Hospital Partnerships — Pilots, Onboarding, Integration Support 25%

Operations & Legal — HIPAA, BAAs, Infrastructure 10%

18-month target: Production platform deployed · 3–5 hospital partners live · First clinical validation published · SaaS revenue started

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Let's Talk

The Prototype Works.
The Architecture is Proven.

We've built the hardest part — a self-tuning, federated ML engine that works on real clinical standards. Now we need capital to deploy it into hospitals, validate it on real patient outcomes, and grow the network.

Contact Founder investors@cixplatform.com

cixplatform.com · Confidential 2025

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