99% of AI projects fail at scale. We help you build the 1% that succeed.
AI hit the datasphere like a storm. But scaling AI/ML and LLMs requires solid ground. We help you build your data foundation to support real progress.
What a stronger data foundation unlocks.
Improved revenue from AI-ready data
Better customer retention with mature data architecture
AI is a broad and evolving collection of disciplines.
AI is a broad and constantly evolving collection of disciplines, including ML, LLMs, Agentic AI, and others.
We help you make thoughtful choices about the infrastructure, processes, and technologies underpinning your long-term data strategy, starting with the critical data foundations.
Most organizations rush to scale AI, but progress stalls when the data foundation isn’t AI-ready.
AI success hinges on solid data foundations and the right partners to deliver business value.
What are the greatest risks and rewards of layering AI/ML into your infrastructure?
We worked with IDC to uncover the core elements companies need to get a headstart with AI data strategy. IDC’s InfoBrief explores how, and why, AI success hinges on solid data foundations and the right partners to deliver business value.
The Path to AI-Ready Data
How, and why, AI success hinges on solid data foundations and the right partners to deliver business value.
Four ways we build the 1% that succeed.
AI/ML Strategy
Identify high-impact use cases and create a tailored AI/ML roadmap aligned with business objectives. We apply product management principles to identify and develop high-value cognitive computing use cases.
Once we’ve homed in on the best combination of practices, methodologies, and tools, we share our observations through a custom implementation plan. It works whether you’re on legacy infrastructure or born in the cloud.
- Use Case Discovery Workshops
- AI/ML Roadmap Design
- Project, Program & Portfolio Management
- Continuous Improvement Plans
AI-Data Foundation Readiness
Once you’ve identified high-impact use cases and are ready to move forward with a roadmap, we help you architect your data foundations to support AI. This work makes AI into an “add-on” to your environment rather than a complex start-from-scratch endeavor.
We ensure your data is clean and structured to support scalable, high-performance AI/ML solutions in the long term.
- Data Auditing and Profiling
- Data Pipeline Engineering
- Feature Discovery Workshops
- ETL and CDC Optimization
Predictive Modeling and Deployment
Apply AI-based predictive analytics to forecast trends, understand customer behavior, and identify operational risks with accuracy.
From initial design to production launch, we anchor AI/ML-driven forecasts into your daily operations, whether you’re using predictive for Sales and Marketing, Finance, Research and Development, or other critical business units. We ensure your models stay accurate and deliver ongoing value.
- Model Design and Monitoring
- CI/CD Pipelines for ML Workflows
- Supervised and Unsupervised Learning
AI Integration and Automation
Five years ago was the best time to get your data ready for AI. Today is the second best time.
We plug advanced capabilities into your current stack to boost what you already have, without disruption. We embed data governance into the engineering, with robust standards and controls to increase efficiency and lower risk.
- GenAI and Conversational AI Integration
- Metadata Extraction and Cataloging
- Integration with Existing Systems
- Automated Quality Checks
- Policy-based Access Controls Using Zero Trust Security Principles
What is AI, and where can you apply it purposefully?
Four applications where DI Squared helps organizations move from hype to durable, governed value.
Critical Data Foundations for AI-Readiness
Data is scattered, inconsistent, and unreliable, causing delays and blockages across the board, including in analytics and AI projects. We help unify and clean data by building trusted, governed foundations.
Production-Grade Machine Learning
Many companies struggle to turn ML prototypes into trusted tools because of messy data, unclear ownership, complex integration, and missing monitoring. We help deliver reliable ML through strong data foundations and governance.
Accurate, Trustworthy Generative AI
LLMs, and other GenAI tools, deliver impressive outputs but risk hallucinations, privacy breaches, and unpredictable costs without robust grounding and controls. We help secure and optimize your GenAI tools with governance, grounding, and cost management.
Purposeful Agentic AI
Agentic AI promised to automate complexity, like a chatbot that handles FAQs, or helps scientists conduct analyses, boosting efficiency by reducing human effort. But fragmented data and poor system links are the Achilles’ heel of true agentic AI. We help implement safe, reliable agents with guardrails and controls.
With DI Squared Qlik implementation best practices, we’ve met our project goal of implementing an enterprise-wide information management system with matured data infrastructure to provide accurate and timely analytics/metrics/reporting.
Margo L. Hershberger
Our take on the brave new world of cognitive computing solutions.
Risk Management for the People Part of AI.
Everyone's racing to adopt AI, but they're forgetting the drivers. Learn techniques to make sure your people are in the driver's seat.
Refresher: How to Avoid Common Pitfalls of ML Projects.
A practical, scientific approach to selecting use cases, validating them with your data, and automating decisions with real-time signals.
Time Series Forecasting With Cross-Industry Examples.
Explore statistical frameworks and advanced ML, with practical, hands-on examples to identify the optimal forecasting strategy.
It takes as long as a cup of coffee to get started.
Book a 30-minute call with a DI Squared consultant. We will listen first, then tell you whether the right next step is a strategy conversation, a data-foundation audit, or something else entirely.