Data, Automation, & AI

Most hospitals and health plans don't have a data problem so much as a fragmentation problem. Clinical data lives in the EHR. Claims and eligibility live in the core administrative platform. Utilization data sits in a UM system. Infrastructure telemetry lives somewhere else entirely. Each is accurate in isolation and contradictory in aggregate.

We design and operate the architecture that resolves this:

• Unified data foundation — cloud or hybrid data platforms sized to your actual workloads, not a vendor's reference diagram

• Canonical data models - aligned to healthcare standards (FHIR, HL7v2, X12, USCDI) so downstream consumers aren't each writing their own translation logic

• Data governance and lineage — documented ownership, quality thresholds, and traceability that hold up under audit

• Master data and identity resolution - across patient, member, provider, and facility records

• Security and access controls - built to HIPAA and HITRUST expectations, with role-based access and full audit trails

The outcome: one reliable view of cost, quality, risk, and operational performance — and a foundation automation and AI can safely be built on.

Intelligent Analytics & Workflows
Insight is only valuable when it triggers action.

Reporting tells you what happened. Intelligent workflows act on it. We build the layer where analytics and operations meet, so findings don't sit in a dashboard waiting for someone to notice them.

Analytics we deliver

• Operational and financial performance reporting for executive and departmental leadership

• Quality and regulatory measure tracking, including HEDIS and Stars program support

• Utilization, network, and cost-of-care analytics for health plans

• Capacity, throughput, and length-of-stay analytics for provider organizations

• Predictive models for readmission risk, no-show likelihood, denial probability, and infrastructure failure

Workflows we automate

• Prior authorization intake, documentation gathering, and status routing

• Utilization management triage and clinical review queue prioritization

• Claims edit resolution and denial rework routing

• Eligibility and benefits verification

• Provider data maintenance and roster reconciliation

• IT service management — ticket classification, routing, provisioning, access requests, and patch orchestration

Where AI is appropriate, we apply it with clear boundaries: models assist and prioritize, humans decide. Every automated decision path is documented, monitored for drift, and reversible. Clinical judgment stays with clinicians.

Real-Time Integrations
Batch files can't support real-time care decisions.

A nightly extract is adequate for retrospective reporting and inadequate for almost everything else. Care coordination, authorization turnaround, bed management, and member service all depend on knowing what is true right now.

We build and manage event-driven integration:

• Streaming and event architecture— ADT feeds, order and result events, claims status changes, and authorization updates delivered as they occur

• FHIR-based APIs and subscriptions - for modern application interoperability

• Interface engine design and management - (Rhapsody, Mirth, Cloverleaf, and equivalents), including migration off aging interface estates

• Bi-directional integration - between EHRs, payer platforms, care management tools, IVR, and CRM systems

• Monitoring and reconciliation — message-level observability, alerting, and automated replay so a silent interface failure doesn't become a patient safety event

The result is a connected environment where information reaches the right system and the right person at the moment it matters.

Connecting Legacy Applications via Standard APIs
You don't have to replace it to modernize it.

Every health system and plan runs applications that are too embedded, too expensive, or too regulated to retire on a convenient timeline. Those systems are usually the reason modernization stalls — and they don't have to be.

We put a modern interface in front of what you already own:

• API enablement of legacy platforms — REST and FHIR façades over systems that predate both

• Protocol and format translation - between flat files, HL7v2, EDI, proprietary interfaces, and modern JSON APIs

• API management and gateway operations — authentication, rate limiting, versioning, developer documentation, and usage monitoring

• Robotic process automation - where no interface exists at all, used deliberately as a bridge rather than a permanent architecture

• Incremental modernization roadmaps that sequence migration around clinical and financial risk, not vendor pressure

This is the fastest path to interoperability for most organizations: unlock the data trapped in legacy systems now, and decommission on a schedule your operations, budget, and compliance obligations can actually absorb.

Why deliver this as a managed service

Building these capabilities internally means recruiting data engineers, integration specialists, ML practitioners, and platform operators into a market where healthcare organizations compete against technology companies for the same talent — and then retaining them.

As a managed service, you get:

• Speed— proven architectures and reusable integration patterns instead of a first-time build

• Continuity — 24/7 operations, monitoring, and support with no single-person dependencies

• Predictable economics — operating expense in place of large capital projects and uncertain internal cost

• Compliance by default — HIPAA-aligned controls, documented processes, and audit-ready evidence built into how the service runs

• Accountability — defined SLAs and measurable outcomes: turnaround time, cost per transaction, uptime, denial rate, and staff hours returned