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ACI Infotech

MLOps for Healthcare — HIPAA-Compliant ML Pipelines

Deploy clinical prediction models, patient risk scores, and medical imaging ML with HIPAA governance.

Databricks Elite Partner
MLflow Specialist
AWS Partner
Azure Partner
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Is Your ML Stuck in Notebooks?

PHI in ML Pipelines

Training data contains PHI but there's no governance on how it flows through ML experiments.

Clinical Validation Gaps

Models need clinical validation before deployment—no standardized process exists.

Slow Research-to-Production

Months between research model validation and clinical deployment due to manual processes.

No Model Monitoring

Clinical prediction models in production with no drift detection or performance alerts.

0
Compliant MLOps
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Faster Clinical ML
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PHI Governance
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Model Monitoring

Production-Grade MLOps

We implement the full MLOps lifecycle on Databricks — from experiment tracking to model monitoring.

01

Assess

Evaluate your MLOps maturity and identify the biggest gaps between development and production.

02

Build

Implement MLflow tracking, Feature Store, and Model Registry with proper governance.

03

Automate

CI/CD pipelines for model training, validation, and deployment using Databricks Workflows.

04

Monitor

Production monitoring for data drift, model performance, and automated retraining triggers.

What You Get

MLflow Foundation

Experiment tracking, model registry, and deployment pipelines — all integrated with your lakehouse.

Feature Store

Centralized, governed features shared across teams with point-in-time correctness.

Automated Pipelines

End-to-end ML pipelines from data prep to model serving, triggered by schedules or events.

Production Monitoring

Real-time dashboards for model performance, data drift, and prediction quality.

Proven Results

Real outcomes from organizations like yours.

50 Models to Production

Implemented MLOps platform that took a retail company from 3 production models to 50 in 6 months.

retail

Real-Time Fraud Scoring

Built an MLOps pipeline that deploys and monitors fraud models serving 10,000 predictions per second.

finance

Frequently Asked Questions

MLflow is the open-source ML lifecycle platform built into Databricks. It tracks experiments, manages model versions, and automates deployment.
Yes. We integrate MLflow with GitHub Actions, Azure DevOps, Jenkins, or any CI/CD system your engineering team uses.
Databricks Model Serving provides serverless endpoints for real-time predictions with autoscaling and A/B testing built in.
Unity Catalog governs ML models alongside data—access controls, lineage, and approval workflows for model promotion.

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ACI Infotech
Microsoft Partner•AWS Partner•Snowflake Partner
Privacy PolicyTerms© 2026 ACI Infotech