DSC helps companies turn data into working AI and ML solutions, from data readiness assessment to the development, deployment, and support of models for forecasting, classification, and business process automation. As part of our AI consulting services, we combine machine learning consulting with hands-on delivery, building custom machine learning models for predictive analytics and integrating them directly into your existing data platform. Whether you need an AI readiness assessment, a full AI strategy consulting engagement, or support with machine learning implementation and MLOps services, our team stays involved through deployment, monitoring, and retraining, not just the proof of concept.
Many companies invest in AI and machine learning, but never see the results they expected. These are the challenges we see most often:
From assessing your data’s readiness to keeping models performing in production, DSC covers every stage of the AI/ML lifecycle.
Before developing models, DSC assesses the client’s data readiness and prioritizes the use cases with the greatest potential impact.
We build predictive models that support day-to-day business planning and decision-making.
We develop and validate ML models tailored to your specific business tasks, from prediction to automation.
DSC doesn’t just build models; we ensure their stable operation after deployment.
At DSC, AI and ML aren’t standalone technical exercises; they’re tools that make business decisions faster, more accurate, and easier to scale.
Our AI/ML services are built to deliver measurable business value, not just technical output.
A clear, structured approach, not a chaotic set of tasks, so every AI/ML engagement moves from idea to production with confidence.
Our AI and ML solutions are built on a proven stack of languages, cloud platforms, and MLOps tools, connected to a solid data foundation.
Data EngineeringDSC delivered a comprehensive financial data overhaul, building out advanced reporting, automating manual processes, and tightening data quality across the board.
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Data EngineeringAutomated complex survey analytics by centralizing MySQL and PostgreSQL data in Snowflake, modeling with dbt, and delivering scalable, interactive Tableau dashboards with advanced statistical workflows.
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Data EngineeringUnified multi platform marketing and lead generation data into Snowflake using Airbyte and dbt, delivering scalable Tableau dashboards for executive, affiliate, and operations teams.
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Data and Cloud MigrationsMigrated GA4 and Magento ingestion workflows from Fivetran to self hosted Airbyte to reduce integration costs and improve control, flexibility, and customization of pipelines.
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Dashboard DevelopmentIntegrated Microsoft Dynamics, E21, and Chempax into Snowflake and delivered real time Finance and Sales dashboards in Power BI to enable unified, granular, and year over year business insights.
View Case StudyThese services connect to build a complete, reliable data foundation for your business.
DSC’s AI and ML consulting spans the full lifecycle from assessing data readiness, to developing and validating models, to deploying and monitoring them in production.
Traditional analytics reports on what has happened, while AI and ML consulting focuses on building models that forecast outcomes, classify data, and automate decisions going forward.
The right data depends on the use case, but models generally need clean, structured, and sufficiently complete historical data, something DSC evaluates during the readiness assessment.
Timelines vary by project scope and data readiness, but most engagements move from assessment to a production-ready model over the course of a few months.
Yes. DSC builds models that integrate directly into your current data platform rather than requiring a separate system.
DSC works with major cloud platforms and adapts to the environment your organization already uses.
We put monitoring, validation, and quality checks in place so prediction accuracy is tracked continuously, not just at launch.
MLOps refers to the practices and tooling that keep machine learning models reliable in production, including deployment automation, monitoring, and retraining. Without it, models can quietly degrade in accuracy over time.
Yes. DSC can add a predictive layer to dashboards you already use, so forecasts and predictions sit alongside your existing metrics.
DSC ties AI use cases to specific business outcomes, such as forecast accuracy or reduced manual effort, so the value can be measured against a clear baseline.
Yes. NLP and text analysis are part of our machine learning model development services, applied where they fit the client’s specific use case.
DSC provides ongoing monitoring, retraining, and drift control after deployment to keep models accurate and reliable over time.
If your company wants to forecast demand, automate decisions, or implement AI without the risk of getting stuck at the pilot stage, DSC will help build a practical AI roadmap and bring models to production. Let’s start with an assessment of your data readiness.
