Healthcare AI Platform for Multi-Clinic Operations

Ottawa Healthcare Network Gains Operational Visibility with CareOps AI OS

A growing multi-location healthcare network in Ottawa struggled with fragmented operational data spread across EHR, telehealth, scheduling, and billing systems. DATAFOREST implemented CareOps AI OS — an operational intelligence platform that unified data across 5 core systems, standardized workflows, and gave leadership real-time visibility into patient flow, provider utilization, and bottlenecks. The result was faster decision-making, better scheduling efficiency, reduced manual coordination, and a stronger foundation for scalable clinic operations.

Healthcare

Operational Intelligence

AI-Driven Healthcare Management

reduction in manual operational coordination

faster operational decision-making

The client is a multi-location healthcare provider based in Ottawa, operating several clinics and care teams across different locations. The organization provides consultations, diagnostics, and long-term care programs.

FastApi

Langchain

OpenAI GPT

Qdrant

Databricks

THE CHALLENGE

Operational Fragmentation Across a Growing Healthcare Network

As the organization scaled across multiple clinic locations, its operations became increasingly fragmented. Core workflows were spread across disconnected systems, making it difficult to maintain consistency, monitor performance, and coordinate care efficiently. Leadership lacked a unified operational view of what was happening across locations, which limited fast, informed decision-making.
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The organization needed a platform capable of connecting existing systems, standardizing processes across teams, and providing actionable operational insights.
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The goal was to create a central operational control layer capable of coordinating data, workflows, and decision-making across the healthcare network.

Disconnected operational systems

Critical data was spread across EHR, telehealth, scheduling, and billing platforms, creating silos and limiting visibility across the network.

Inconsistent workflows between locations

Different clinics and care teams followed different processes, making operations harder to manage and standardize at scale. Integrations between platforms were incomplete or inconsistent.

Limited real-time visibility for leadership

Decision-makers could not reliably track patient flow, provider utilization, or operational bottlenecks across clinics in one place. Leadership teams relied on delayed reports rather than real-time insight.

Manual coordination overhead

Teams had to rely on manual effort to align processes, gather information, and resolve day-to-day operational inefficiencies. Operational bottlenecks were difficult to identify at their root cause.

THE SOLUTION

CareOps AI OS for Unified Healthcare Operations

DATAFOREST implemented CareOps AI OS, an operational intelligence platform designed to connect the provider’s existing systems into one unified operational layer above existing healthcare systems. The solution consolidated data across 5 core platforms, standardized workflows across locations, and delivered real-time visibility into clinic performance, provider utilization, and patient flow. This created a stronger operational foundation for scalable, data-driven healthcare management.

Cross-system operational data unification

The first step was building a unified healthcare data model that consolidates information from existing systems.

Data from EHR platforms, telehealth services, scheduling tools, and operational systems was collected, reconciled, and structured into a consistent operational dataset.

This created a reliable foundation for operational analytics and workflow orchestration.

The platform introduced a structured integration inventory, identifying how each operational system interacted with others.

Real-time operational visibility

Leadership teams gained access to real-time operational dashboards showing key metrics across locations.

These dashboards provide visibility into:
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patient flow and appointment preparation
provider workload and utilization
scheduling performance
operational bottlenecks

Instead of relying on historical reporting, leadership can now monitor operational performance in real time.

Workflow standardization across locations

CareOps AI also introduced standardized operational procedures (SOPs) across teams and shifts.

This ensured that operational processes remained consistent across locations and reduced variability in how teams handled scheduling, patient preparation, and internal coordination.

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Predictive scheduling and capacity optimization

CareOps AI introduced predictive models designed to improve appointment scheduling and resource utilization.

These models analyze historical appointment patterns, no-show probabilities, and demand fluctuations to optimize schedules and improve provider utilization.

This allows clinics to anticipate operational pressure before it appears.

THE RESULT

AI-Driven Operational Platform for Healthcare

Reducing admin load, stabilizing workflows, and increasing capacity

Dataforest transformed fragmented operations into a unified, AI-driven system by consolidating data, automating workflows, and enabling real-time operational visibility.
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Key outcomes included:

100% unified operational data model
Data from EHR, telehealth, scheduling, and communication systems was consolidated into a single structured dataset, eliminating fragmented reporting.
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Single Source of Truth across 5 core systems
Reliable integrations created one synchronized operational layer used by both operations teams and leadership.
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Real-time operational visibility
Dashboards replaced delayed reporting, enabling immediate identification of issues in patient flow, scheduling, and utilization.
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AI-driven workflow automation
Operational processes were automated, reducing manual coordination and improving execution consistency.
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Predictive scheduling & capacity optimization
Data-driven allocation of appointments improved provider utilization and reduced idle time.
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Standardized workflows across locations
Unified SOPs ensured consistent operations across teams, shifts, and clinics.
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Additional Value Delivered:

Reduced operational friction
Teams no longer rely on manual coordination between systems.
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Improved patient experience
Better preparation and smoother scheduling reduced delays.
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Scalable operational foundation
System supports multi-location growth without increasing complexity.
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KPIs

35%

less administrative workload through automation

25%

reduction in operational bottlenecks

5 systems

unified into a single operational data model

Healthcare AI Platform for Multi-Clinic Operations

How we provide data integration solutions

Step 1 of 5

Free consultation

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

Step 2 of 5

Discovering and feasibility analysis

One of our core values is flexibility, hence we work with either one page high level requirements or with a full pack of tech docs.

At this stage, we need to ensure that we understand the full scope of the project. We receive from you or perform a set of interviews and prepare the following documents: integration pipeline (which data we should get and where to upload), process logic (how system should work); use cases and acceptance criteria; solution architecture. Ultimately we make a project plan which we strictly follow.

Step 3 of 5

Solution development

At this stage, we build ETL pipelines and necessary APIs to automate the process. We attract our DevOps team to build the most efficient and scalable solution. Ending up with unit tests and quality assurance tests to ensure that the solution is working properly. Focus on Results is one of our core values as well.

Step 4 of 5

Solution delivery

After quality assurance tests are completed, we deliver solutions to the client. Though we have over 15 years of expertise in data engineering, we are expecting client’s participation in the project. While developing the integration system, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high-level of communication is also our core value.

Step 5 of 5

Support and continuous improvement

We understand how crucial the solutions that we code for our clients are! Our goal is to build long-term relations, so we provide guarantees and support agreements. What is more, we are always happy to assist with further developments and statistics show that for us, 97% of our clients return to us with new projects.

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~50%

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System Integrations Completed

100%

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