Ataira

Scalable AI Integration and Automation Consulting

Ataira delivers scalable AI integration and automation consulting that connects AI, machine learning, and agentic workflows to your existing data, applications, and cloud platforms, helping organizations modernize operations, reduce manual effort, and unlock new analytics-driven decision-making

AI Integration & Automation Services

Ataira embeds machine intelligence into business workflows, integrating ML models, deploying agentic automation, and delivering AI-as-a-Service so teams can reduce manual effort and make data-driven decisions. We focus on explainability, secure operations, and measurable business outcomes.

Our Scalable AI Integration and Automation Consulting offerings are often delivered alongside complementary practices such as Data Analytics Consulting, Data Engineering Services, and Cybersecurity and Compliance to ensure AI initiatives are secure, explainable, and grounded in reliable data.

Healthcare Analytics Platform Case Study

Executive level monitoring of Traditional MIPS and Pathology MVP performance

MIPS Pathology Requirements Tracking | Executive Dashboard

Aggregated MIPS readiness across Quality, Improvement Activities, Promoting Interoperability and Cost

Customer Background

A regional pathology group supporting multiple hospital and ambulatory sites needed a single view of Merit-based Incentive Payment System (MIPS) performance. Historically, Quality, Improvement Activities, Promoting Interoperability, and Cost results were tracked in separate spreadsheets, registry portals, and billing reports, making it difficult for leadership to understand incentive readiness or compare Traditional MIPS with emerging pathology-specific MVP options.

Objective

The objective was to build an executive dashboard that consolidates pathology MIPS performance at the practice level, supports a full switch between Traditional MIPS and the Pathology MVP, and clearly shows how readiness in each performance category contributes to the projected MIPS Final Score. The solution needed to be transparent, auditable, and aligned with College of American Pathologists guidance while preserving strict de-identification of patient data.

Approach

  • Data Integration and Normalization - Combined EHR, LIS, billing, and registry extracts into a curated analytics model keyed to MIPS numerators and denominators, low volume thresholds, and CAP pathology measure specifications.
  • Measure Mapping - Mapped pathology quality measures, Improvement Activities, Promoting Interoperability measures, and CMS cost indices to a consistent semantic layer, supporting both Traditional MIPS and the Pathology MVP scoring model.
  • AI-enabled Analytics - Implemented an AI agent that scans de-identified data for measure logic anomalies, missing synoptic fields, and scoring edge cases, providing coaching insights directly in the dashboard.
  • Executive Dashboards - Delivered the executive view shown above, with KPI cards, six visualizations, and an AI insights panel, all designed to help clinical and operational leaders understand where to invest effort before the submission deadline.

Outcomes

  • Consistent, practice-level view of pathology performance across Quality, IA, PI, and Cost in a single dashboard.
  • Improved clarity on the tradeoffs between remaining on Traditional MIPS versus moving to the Pathology MVP.
  • Reduction in manual MIPS reconciliation work through AI-assisted data validation and measure coaching.
  • Increased confidence that projected MIPS Final Scores accurately reflect underlying pathology quality and operational performance.

AI/ML Model Integration

AI/ML Model Integration

Seamlessly integrate advanced AI and machine learning models into your business applications. Our team helps you select, customize, and deploy models that drive smarter decisions and automate complex tasks.

  • Model selection and customization for your business needs
  • Integration with existing software and workflows
  • Data preparation and pipeline setup
  • Ongoing monitoring and optimization

AI/ML Model Integration delivers the most value when paired with strong data pipelines, governed analytics, and secure cloud operations, which is why many organizations combine it with our Data Analytics Consulting, Data Engineering Services, and Cybersecurity and Compliance.

Agentic AI for Business Process Automation

Agentic AI for Business Process Automation

Automate repetitive and complex business processes with agentic AI solutions. We design and implement AI agents that handle tasks, interact with systems, and adapt to your evolving business needs.

  • Process analysis and automation strategy
  • Custom AI agent development
  • Integration with business applications and APIs
  • Continuous improvement and support

Agentic AI for Business Process Automation performs best when it is connected to high-quality data and trusted insights, so we typically align these solutions with our Data Engineering Services, Data Analytics Consulting, and AI Automation Integration to create resilient, end-to-end automation.

AI-as-a-Service (AIaaS) Deployment

AI-as-a-Service (AIaaS) Deployment

Deploy scalable AI solutions without the overhead of infrastructure management. Our AIaaS offerings let you access powerful AI capabilities on demand, tailored to your business requirements.

  • Consulting on AIaaS platform selection
  • Deployment and configuration of AI services
  • Integration with your data and workflows
  • Ongoing management and optimization

AI-as-a-Service (AIaaS) Deployment is even more effective when it is fed by reliable data engineering, governed analytics, and secure cloud controls, making it a natural fit alongside our Data Engineering Services, Data Analytics Consulting, and Cybersecurity and Compliance.

Frequently Asked Questions

What do enterprise AI integration services deliver?

You receive a deployed model-serving architecture, secured API endpoints for prediction access, orchestration connecting AI outputs to business systems, and monitoring for latency, throughput, and traceability. Predictions become auditable production decisions.

How does agentic AI automate multi-step processes?

Agentic AI is delivered as controlled workflows: defined action boundaries, system connectors, state management, audit logging, and human-in-the-loop checkpoints. Manual process steps are replaced without losing governance.

How are production AI models monitored and retrained?

Models are instrumented for drift, accuracy, and data skew. Alert thresholds trigger investigation. Retraining pipelines promote versioned models through canary deployment. You maintain continuous performance with audit trails.