Moving AI From Pilot to Production With Governance and Integration
Rationalizing Hybrid Data Environments to Reduce Complexity
- Service: AI Enablement & Intelligent Systems
- Industry: AI Enablement & Intelligent Systems
- San Francisco, California
Executive Summary
AI creates value only when deployed responsibly and integrated into real workflows. This success story showcases how Sloancode helped a healthcare technology organization based in San Francisco, California, move AI from stalled pilots into production-ready systems.
Client Overview
Our client, a growth-stage healthcare technology company, faced significant challenges:
- AI pilots produced demos but did not scale to production
- Governance concerns blocked deployment
- AI systems were disconnected from operational workflows
The Challenges
- Proofs of concept failed to integrate with systems of record
- Lack of governance created risk, slowing executive approval
- ROI remained unclear due to poor workflow fit and missing measurement
Implementation Process
Planning
Assessed AI readiness, identified viable use cases, and defined governance requirements.
Execution
Designed an AI system architecture integrated into business workflows with measurable outcomes.
Testing
Validated accuracy, reliability, security controls, and escalation paths.
Deployment
Rolled out AI into production with monitoring and operational ownership.
The Solution Provided
We delivered a governed intelligent system solution:
- AI Use-Case Prioritization:Selected operationally viable AI use cases
- Intelligent System Design:Integrated AI into workflows, not standalone tools
- Governance + Controls:Implemented oversight, monitoring, and risk controls
Technologies, Methodologies, or Strategies
- AI Architecture:Retrieval-augmented systems (RAG), decision-support patterns
- Data Integration:Secure connectors to operational data sources
- Governance:Human-in-the-loop escalation, auditability
- Monitoring:Performance tracking and continuous improvement loops
Explanation of Technologies and Strategies
We chose governed AI system design to ensure AI could operate safely in production. By integrating AI with real workflows and adding controls for oversight and monitoring, the organization moved from pilots to measurable operational value.
Technology Stack
Results Achieved
- AI moved from pilot to production deployment
- Reduced operational friction through workflow automation
- Improved governance posture and executive confidence
Team Members and Skillsets
- 1 AI Program Lead (AI delivery, governance)
- 1 AI Engineer (RAG systems, integration)
- 1 Data Engineer (Data access, quality, pipelines)
- 1 Security / Governance Lead (Controls, auditability)
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