From Black-Box APIs to Agentic Control: A Case Study in Building Production-Grade Gen AI Systems for Healthcare

One-liner summary:
The client lacked a unified, secure AI foundation to build proprietary LLMs and deploy production-grade AI agents at scale.
Industry
Healthcare
Location
Florida, USA
Tech Stacks

Azure

Challenge

A leading healthcare provider partnered with Ideas2IT to deploy a HIPAA-compliant Agentic AI Architecture featuring private LLMs, secure context pipelines, and autonomous agents that improved clinical triage efficiency by 40%.

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The Problem with the Status Quo

For this leading healthcare organization, AI adoption was a strategic transformation. The executive team set out to establish Agentic AI as foundational infrastructure supporting scalable, compliant deployment of intelligent agents across clinical and operational functions.

They aimed to build a production-grade architecture where agents could reason, act, and evolve using institutional knowledge within regulated workflows.

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Where the Gaps Were

  • No agent hosting layer to support orchestration and routing at production scale
  • Reliance on public LLM APIs, limiting traceability, compliance, and customization
  • No vectorized context layer to retrieve institutional knowledge
  • No governance stack for lifecycle management, auditing, or PHI-safe operations

Architecting intelligent agents without these foundations risked compliance failures and patient safety concerns.

What We Delivered

Ideas2IT delivered a production-ready Agentic AI stack in under 10 weeks, designed specifically for the client’s infrastructure, compliance, and security requirements.

Core System Components:

  • LLM Layer: Fine-tuned transformer models (via LoRA) trained on clinical and operational data
  • Context Engine: FAISS-based vector store structured around domain-specific ontologies
  • Agent Framework: Containerised, lifecycle-managed agents with routing, triage, and annotation capabilities
  • Execution & Governance Plane: RBAC enforcement, prompt logging, observability dashboards, and human-in-the-loop modules
  • Secure Deployment: Fully encrypted and hosted on Kubernetes with built-in audibility

Outcomes We Achieved

Area Outcome
Billing cycle time Reduced from 45 days to fewer than 10 days
Release velocity Weekly rollouts enabled via CI/CD
Clinical data workflow Migrated to AI-assisted, browser-native environment
Partner integrations Expanded to 6+ platforms including ERP and CRM
Developer productivity Improved through service isolation and modular code
Industry
Healthcare
Location
Florida, USA
Tech Stacks

Azure

Challenge

A leading healthcare provider partnered with Ideas2IT to deploy a HIPAA-compliant Agentic AI Architecture featuring private LLMs, secure context pipelines, and autonomous agents that improved clinical triage efficiency by 40%.

‍

Key Takeaways

  • Agent-first foundation: Built specifically to support autonomous reasoning and action
  • Domain-specific training: Models were tuned on internal, regulated data
  • Integrated governance: RBAC, audit logs, and HITL feedback loops were included by default
  • ‍Composable architecture: Each layer is modular, traceable, and independently scalable

Co-create with Ideas2IT

We show up early, listen hard, and figure out how to move the needle. If that’s the kind of partner you’re looking for, we should talk.
We’ll align on what you're solving for - AI, software, cloud, or legacy systems
You'll get perspective from someone who’s shipped it before
If there’s a fit, we move fast — workshop, pilot, or a real build plan
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