AI & Machine Learning Consulting ServicesPurpose Built AI & MLCreate new capabilities and transform your organization with artificial intelligence by establishing an AI strategy, building practical ai solutions and operationalizing machine learning models all supported by strong ml ops and lifecycle management. Talk to Concurrency Custom AI and Machine Learning Consulting & DevelopmentEstablish Your AI StrategyDefine a clear roadmap for how artificial intelligence will create value for your organization, aligning AI initiatives with business goals and priorities. Build Practical AI SolutionsDevelop and deploy AI-powered applications tailored to real business needs, driving innovation and measurable outcomes. Operationalize Machine Learning ModelsMove machine learning models from experimentation to production, ensuring they deliver ongoing value through robust MLOps and lifecycle management. Common AI Development & Implementation Challenges We SolveAlign AI to Your Business Defining a clear AI strategy that aligns with business goals and delivers measurable value.Business Value Focused AI Developing practical AI solutions that address real business needs and drive innovation.Production-Ready ML Models Moving machine learning models from experimentation to production, ensuring robust MLOps and lifecycle management.Responsible AI Governance & Development Ensuring responsible governance, security, and compliance throughout the AI and ML implementation process.Ready to talk to us about building AI that actually delivers business value?Let’s Talk!!AI & Machine Learning Consulting Services AI Strategy & Value Roadmap Turn AI ambition into a clear, executable plan. Learn More Natural Language Solutions Enable systems that understand and respond like humans. Learn More Generative AI & RAG Solutions Ground generative AI in your data—safely and responsibly. Learn More Predictive ML Models Anticipate outcomes and make smarter decisions. Learn More Detection ML Models Identify anomalies, risks, and issues before they escalate. Learn More MLOps & Model Lifecycle Management Move models from experimentation to production—with confidence. Learn More AI Strategy & Value Roadmap Natural Language Solutions Generative AI & RAG Solutions Predictive ML Models Detection ML Models MLOps & Model Lifecycle Management AI Strategy & Value RoadmapTurn AI ambition into a clear, executable plan. Learn More Natural Language SolutionsEnable systems that understand and respond like humans. Learn More Generative AI & RAG SolutionsGround generative AI in your data—safely and responsibly. Learn More Predictive ML ModelsAnticipate outcomes and make smarter decisions. Learn More Detection ML ModelsIdentify anomalies, risks, and issues before they escalate. Learn More MLOps & Model Lifecycle ManagementMove models from experimentation to production—with confidence. Learn More AI Strategy & Value RoadmapAI Strategy & Value Roadmap helps organizations define how artificial intelligence will deliver real business value. We work with leaders to identify high‑impact use cases, align AI initiatives to business priorities, and create a practical roadmap that balances quick wins with long‑term capability building.Define a clear AI vision aligned to business goalsPrioritize use cases based on value, feasibility, and riskEstablish governance, security, and responsible AI guardrailsCreate a phased roadmap from pilot to enterprise scale Natural Language & NLP SolutionsNatural Language Solutions leverage AI to interpret, generate, and interact using human language. We help organizations apply natural language capabilities to real business scenarios—improving access to information, automating interactions, and enhancing user experiences.Enable conversational and language‑driven experiencesExtract meaning and intent from unstructured textImprove access to information through natural language interfacesApply NLP to real workflows and business processes GenAI Knowledge & Assistant Solutions (RAG)GenAI Knowledge & Assistant Solutions use Retrieval‑Augmented Generation (RAG) to deliver accurate, context‑aware responses based on your enterprise data. We help organizations build assistants that answer questions, surface insights, and support decisions—without hallucinations or data leakage.Ground generative AI in trusted enterprise knowledgeImprove accuracy and relevance of AI responsesEnable secure, permission‑aware access to informationDeploy assistants for employees, customers, or operations Predictive ML ModelsPredictive ML Models use historical data to forecast future behavior and trends. We help organizations build and deploy models that support planning, optimization, and proactive decision‑making across key business functions.Forecast demand, risk, or performance trendsSupport planning and optimization with data‑driven predictionsApply machine learning to structured business problemsTurn historical data into forward‑looking insights Detection ML ModelsDetection ML Models focus on identifying unusual patterns, anomalies, or signals that indicate potential problems or opportunities. We help organizations deploy detection models that improve awareness, reduce risk, and support faster response.Detect anomalies and unusual behavior in real timeIdentify risks, defects, or compliance issues earlyMonitor systems and processes at scaleSupport faster investigation and response MLOps & Model Lifecycle ManagementMLOps & Model Lifecycle Management ensures machine learning models deliver ongoing value after deployment. We help organizations operationalize models with monitoring, governance, and automation—so AI solutions remain reliable, scalable, and compliant over time.Operationalize ML models for production useMonitor performance, drift, and model healthAutomate deployment, retraining, and versioningEnsure governance, security, and responsible AI practicesWhy Leading Enterprises Choose Concurrency for AILeading enterprises choose Concurrency to move beyond AI experimentation and build purpose‑built, production‑ready AI that delivers measurable business value. We combine strategic guidance with deep engineering expertise to help organizations align AI to real business goals, build practical solutions, and operationalize machine learning with strong governance, security, and MLOps—so AI scales responsibly, differentiates the business, and continues to deliver value over time. Purpose Built AI & Machine Learning Consulting Frequently Asked Questions What is Purpose Built AI & Machine Learning? Purpose Built AI & Machine Learning focuses on creating AI solutions designed for specific business outcomes—not generic experimentation. It combines AI strategy, practical AI solutions, and production‑ready machine learning models to deliver measurable value with strong governance and lifecycle management. How is purpose‑built AI different from off‑the‑shelf or commodity AI? Commodity AI helps improve baseline productivity, but purpose‑built AI is designed around your data, workflows, and business goals. Purpose‑built solutions integrate directly into business processes, differentiate your organization, and deliver outcomes that competitors can’t easily replicate. Why is an AI strategy and value roadmap important? An AI strategy and value roadmap ensures AI investments are aligned to business priorities and measurable outcomes. Without a clear roadmap, organizations risk fragmented pilots, unclear ROI, and AI initiatives that never scale beyond experimentation. What types of AI solutions fall under Purpose Built AI & ML? Purpose Built AI & ML includes generative AI knowledge assistants (RAG), natural language solutions, predictive machine learning models, detection and anomaly models, and production‑ready AI systems supported by robust MLOps and governance. How does MLOps support long‑term success with AI and machine learning? MLOps ensures machine learning models remain reliable, secure, and effective after deployment. It supports monitoring, retraining, versioning, and governance—allowing AI solutions to scale responsibly, adapt to change, and continue delivering value over time. Case Studies 01 Accelerating Sales Order Processing with AI-Powered Automation 02 Modernizing Manufacturing Analytics with Microsoft Fabric 03 Accelerating Safety Data Sheet Management with AI and Automation 04 Sustaining Digital Momentum Through Governance and Data Readiness 05 Preventing Costly Downtime with AI and Computer Vision 06 Enhancing Manufacturing Efficiency with Microsoft Copilot for M36501Accelerating Sales Order Processing with AI-Powered Automation A leading industrial manufacturer partnered with Concurrency to modernize its manual, error-prone sales order entry process. By implementing a scalable, AI-driven automation platform built on Microsoft Azure, Dynamics 365, and Power Platform, the organization streamlined operations, reduced labor costs, and improved customer responsiveness. Discover how a phased, value-focused approach delivered measurable ROI and laid the foundation for future AI innovation. View Details02Modernizing Manufacturing Analytics with Microsoft FabricA leading industrial manufacturer partnered with Concurrency to overhaul its fragmented analytics environment. By implementing a unified, cloud-based data platform powered by Microsoft Fabric, the organization broke down data silos, empowered business users with real-time insights, and established a foundation for ongoing digital transformation. Discover how thoughtful design, collaborative execution, and robust training led to enhanced decision-making and a stronger data-driven culture. View Details03Accelerating Safety Data Sheet Management with AI and AutomationConcurrency helped a leading chemical manufacturer explore AI-driven solutions to streamline Safety Data Sheet (SDS) authoring, reduce operational risk, and increase throughput—enabling faster product launches and improved regulatory compliance. View Details04Sustaining Digital Momentum Through Governance and Data ReadinessConcurrency partnered with a nonprofit membership association to maintain progress on its digital transformation by empowering product owners, enhancing member experience, and advancing data readiness using Microsoft Fabric. View Details05Preventing Costly Downtime with AI and Computer VisionConcurrency helped a leading energy and logistics provider eliminate costly sand spills by developing a Computer Vision–based IoT solution that detects open truck hatches and triggers real-time alerts—improving safety, efficiency, and reliability. View Details06Enhancing Manufacturing Efficiency with Microsoft Copilot for M365A leading process manufacturer partnered with our team to deploy Microsoft Copilot for Microsoft 365, driving improved data-driven decision-making, enhanced operational efficiency, optimized collaboration, and stronger governance and data security. View Details Previous Next Blog Data & AI Modern Data Architecture in Practice: Lessons from a Collaborative Fabric Rollout January 28, 2026 Derek Steckel Data & AI Why Saying “No” Was the Right Outcome: Lessons from Finding the Right AI Use Case December 10, 2025 Derek Steckel Azure OpenAI, Cloud Datacenter & DevOps, Data & AI, Identity Security and Compliance, Microsoft Teams, Secure Modern Workplace, ServiceNow, Sharepoint, Workplace Modernization Navigating the Agent Revolution: Prepare Your Crew for AI’s Next Wave June 13, 2025 Brian Haydin
