On-Premise Healthcare AI Software

Why On-Premise Matters for Healthcare AI

Healthcare organizations are under increasing pressure to adopt AI tools that improve efficiency and reduce operational costs. At the same time, the regulatory and security requirements for handling Protected Health Information have never been stricter.

For Medicare Advantage compliance programs—particularly those involving HCC validation and chart review—the AI tools you deploy will process some of the most sensitive data in your organization: patient diagnoses, clinical notes, encounter records, and lab results.

The deployment model you choose determines how that data is handled:

Regulatory expectations — HIPAA requires covered entities to evaluate and mitigate risks wherever PHI is processed. On-premise deployment limits the scope of that evaluation to infrastructure you control
PHI sensitivity — Clinical records used for HCC validation contain detailed patient information. Minimizing the number of systems and networks that handle this data reduces breach surface
Breach liability — Every additional party that processes PHI expands your liability chain. On-premise deployment eliminates third-party data processors from the equation
Compliance officer expectations — Internal compliance teams increasingly require documentation showing that AI tools do not transmit PHI outside the organization’s network boundary

On-premise does not mean outdated. CodaFend’s RafCite™ uses the same modern AI capabilities found in cloud tools—containerized deployment, GPU-optimized processing, and structured evidence extraction—without requiring your data to leave your network.

CodaFend’s On-Premise Architecture

RafCite is built from the ground up for on-premise deployment in healthcare environments. Here is what the architecture looks like:

C

Containerized Deployment RafCite ships as container images that run on standard server infrastructure. No custom hardware or proprietary operating system required.

Z

Zero External APIs No data is transmitted to cloud endpoints during processing. All AI inference, evidence extraction, and report generation happens locally.

G

GPU-Optimized Processing Recommended for production throughput. GPU acceleration enables processing charts in under 5 minutes. CPU-only deployment is supported for validation and testing.

U

Managed Updates Software updates are delivered as versioned releases. Your team applies updates on your schedule, with staging validation before production deployment.

Deployment Model

CodaFend follows a structured deployment process designed to minimize risk and ensure your team is prepared to operate the platform independently:

Infrastructure Assessment — CodaFend reviews your server environment, network configuration, and security requirements to confirm compatibility and recommend optimal configuration
Configuration — Application settings are tailored to your environment, including HCC model version preferences, output format, and integration points with your existing review workflow
Installation — Container images are deployed to your infrastructure. CodaFend provides installation support and validates that all components are operating correctly
Validation — Your team processes a set of test charts to verify output quality, review the evidence packet format, and confirm that the system meets your expectations before production use
Go-Live — Production processing begins. CodaFend provides ongoing technical support and delivers managed software updates as new versions are released

Most organizations complete the full deployment process within two to four weeks, depending on infrastructure readiness and internal review requirements.

Security and Compliance Benefits

On-premise deployment provides a simplified compliance posture for organizations that process PHI through AI tools:

Business Associate Agreement — Your BAA is with CodaFend only. No cloud providers or sub-processors are involved in the data path, reducing BAA complexity
Complete audit trail — Every processing step is logged locally on your infrastructure, providing a comprehensive record for internal compliance review and external audit response
Data residency guarantee — PHI never leaves your network boundary. There is no data-in-transit exposure to external systems and no data-at-rest on third-party infrastructure
No third-party processor — CodaFend provides the software; your organization operates it. PHI is processed entirely on hardware you control, eliminating third-party data processing from your compliance chain

Learn more about our zero PHI egress architecture and how it supports HIPAA compliance requirements.

On-Premise vs. Cloud for Healthcare

Both deployment models have legitimate use cases. The right choice depends on your organization’s risk profile, regulatory environment, and operational requirements.

Dimension	Cloud Deployment	On-Premise (CodaFend)
PHI data flow	Transmitted externally	Stays on your network
Third-party processing	Yes	No
Infrastructure control	Vendor managed	Customer controlled
Breach surface	Expanded	Minimized
Pricing	Per-chart / usage	Annual license

For a detailed breakdown, see our full cloud vs. on-premise HCC software comparison.

Infrastructure Requirements

RafCite is designed to run on standard enterprise server hardware. The following are general guidelines—CodaFend provides specific recommendations based on your expected chart volume during the assessment phase.

Operating system — Modern Linux distribution (Ubuntu 22.04+, RHEL 8+, or equivalent) with container runtime support
CPU — Multi-core processor (8+ cores recommended for production workloads)
Memory — 32 GB RAM minimum; 64 GB recommended for concurrent chart processing
Storage — SSD storage with capacity scaled to your chart volume and retention requirements
GPU (recommended) — NVIDIA GPU with 16+ GB VRAM for production throughput. CPU-only deployment is supported but processes charts at reduced speed
Network — Internal network access for chart upload and result retrieval. No external internet connectivity required during processing

Already have server infrastructure? Most organizations with existing on-premise server environments can deploy RafCite on their current hardware. CodaFend’s assessment process confirms compatibility before installation begins.

Frequently Asked Questions

How long does on-premise deployment take?

Most organizations complete deployment within two to four weeks. This includes infrastructure assessment, configuration, installation, and initial validation. CodaFend’s containerized architecture reduces setup complexity compared to traditional on-premise software installations.

What infrastructure is required to run RafCite on-premise?

RafCite runs on standard server hardware with a modern Linux operating system and container runtime. A dedicated GPU is recommended for production throughput but is not required for initial deployment and validation. CodaFend provides specific hardware recommendations based on your expected chart volume during the assessment phase.

Who handles maintenance and updates for on-premise deployment?

CodaFend delivers software updates as managed releases. Your IT team applies updates on your schedule, with the option to validate changes in a staging environment before production deployment. CodaFend provides technical support and documentation for the update process.

Can RafCite run in an air-gapped environment?

Yes. Because RafCite makes no external API calls during chart processing, it can operate in network-restricted or air-gapped environments. Software updates are delivered as offline packages that can be transferred and applied without internet connectivity.