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Major Contender, QE Specialist Services

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Market Glance: Loyalty in Retail, 2Q26, DEOT 4Q25

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Horizon 1 Disruptor, Data Modernization & AI Services, 2026


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Certifications

AI-Driven Modernization
  1. Solutions
  2. Modernization
  3. AI-Driven Modernization

Future-Proof Your Business with AI-Ready Architecture

Break free from the legacy applications and fragmented data silos holding your enterprise back. Revitalize core business applications, legacy data pipelines, and cloud architectures through a semi-autonomous, AI-powered approach that accelerates delivery, lowers TCO, and minimizes engineering effort.

Empower Leadership with Real-Time Data Visibility

Featured Case Study

80% Less Manual Effort With Low-Code Cash Automation

Learn how a global chemical enterprise automated multi-bank cash reconciliation to gain near real-time visibility and strengthen financial control.

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Build Next-Generation Application and Data Estate

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Evolve Legacy Core Systems and Platforms

Migrate monolithic software and costly data environments such as Teradata, Domo, and Tableau to cloud-native architectures, leveraging spec-driven templates to lower TCO while eliminating operational risk.
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Reengineer Codebases and Data Pipelines

Refactor legacy application code and ETL workflows into resilient microservices and high-throughput data streams while preserving critical business logic.
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Migrate Software and Data at Enterprise Scale

Deploy automated discovery, refactoring, and validation frameworks to transfer complex software portfolios and massive datasets with complete operational tracking and human-in-the-loop exception control.
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Transform Advanced Analytics and User Experience

Convert legacy user interfaces and BI dashboards up to 5× faster to modern web platforms, Power BI, and Microsoft Fabric using LLM-powered translation agents.
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Establish Trusted, AI-Ready Foundations

Unify applications and fragmented datasets within a governed, cloud-native environment, embedding continuous validation, security, and lineage mapping to power predictive and agentic AI workloads.

The Value of AI-Powered Modernization

Accelerate Time-to-Value

Accelerate Time-to-Value

Compress deployment timelines by up to 30%, delivering production-ready systems to enterprise stakeholders months ahead of schedule.
Maximize Engineering Productivity

Maximize Engineering Productivity

Reduce manual migration work by 40%, freeing application developers and data engineers to focus strictly on strategic features and innovation.
Drive Confident Decisions

Drive Confident Decisions

Equip executive leadership with real-time operational visibility, highly accurate application telemetry, and trusted business data.
Prepare for Enterprise AI Scale

Prepare for Enterprise AI Scale

Establish clean, highly scalable environments optimized to power predictive analytics, machine learning models, and autonomous AI agents.

Accelerators

Modernize with AI-powered accelerators that simplify migration, reduce risk, and speed cloud adoption.

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QShift
QShift

An AI-driven translation engine that accelerates the migration of costly data platforms like Teradata or legacy Hadoop. QShift automates the semantic conversion of complex SQL, legacy ETL pipelines, and BI visualizations into native cloud data architectures like Snowflake, Databricks, or Microsoft Fabric.

Fast X-MOD_High AI-Q Framework

High AI Qatalyst Framework

Insights

Learn about the newest business trends, technology, and tactics influencing digital transformation.

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Case Study

30% Faster BI Migration to Microsoft Fabric for Chemical Enterprise

An enterprise BI stack was modernized by migrating from Domo to Microsoft Fabric and Power BI, leveraging the proprietary QShift accelerator with automated conversion and confidence-based human validation.

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Case Study

60% Faster Analytics for U.S. Hospital Chain

Discover how an academic medical center cut report latency from 45 minutes to under 5 minutes and increased productivity.

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Case Study

Slashing Retail Data Overhead with Databricks Lake

A top American closeout retailer consolidated legacy enterprise systems into a Databricks data lake, enabling real-time analytics with 40% less manual effort.