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Artificial  Intelligence   Machine Learning

Machine Learning That Moves From Data to Deployment

Helping you build machine learning systems that are robust, scalable, and production-ready.

Start Your ML Journey

Our Expertise

The Right Data,
The Right Process

At UTurn, we make machine learning practical, scalable, and aligned to your business goals. By combining data engineering expertise with proven MLOps practices, we help you move confidently from raw data to deployed models that deliver measurable impact.

Start with your data

Build ML-Ready Data Foundations

Every successful ML initiative begins with high-quality data. UTurn helps you assess and prepare your data to ensure it’s clean, curated, and contextualized for machine learning. We design scalable pipelines that handle ETL, transformation, and feature engineering across structured and unstructured sources—reducing manual effort and improving model reliability. The result is a foundation of high-integrity datasets that accelerate development and minimize downstream risk.

Build Your Model

Engineer Models Built to Evolve

We build reproducible ML workflows designed for experimentation, precision, and scalability. UTurn’s modular approach supports custom model development, tuning, and validation while keeping business KPIs and operational constraints front and center. Our teams engineer models that aren’t just accurate, but adaptable—ready to evolve as data, goals, and conditions change.

Deploy Your Model

Turn Models Into Real-World Impact

Deployment is where machine learning delivers real value. UTurn integrates models into production environments with both real-time and batch inference capabilities, connecting them to business systems, APIs, and user-facing applications. Every model is validated under real-world conditions to ensure reliability, performance, and trust in every prediction.

Manage Your Model

Reliability, Across the ML Lifecycle

Sustaining performance requires discipline. UTurn implements MLOps practices that enable continuous monitoring, versioning, and improvement—supported by CI/CD pipelines for safe updates and automated deployment. Our governance frameworks ensure traceability, compliance, and responsible use, while our Architect-in-Residence (AiR) program provides embedded leadership to guide strategy and scale your ML capabilities.

Service Offerings

End-to-End Machine Learning Services

Accelerate and Operationalize Machine Learning with Confidence

ML - Built Faster and Smarter

UTurn’s ML accelerators are built to help teams move faster from prototype to production, with confidence and clarity. They combine the best of AWS-native services and OSS to simplify the most complex parts of the machine learning lifecycle, including data readiness, model development, deployment, and governance. With proven patterns, reusable components, and automation baked in, they reduce time-to-value and eliminate the guesswork that often slows down innovation.

Accelerator : Demand Forecasting Engine

Demand Forecasting Engine provides a modular framework for building and deploying demand forecasting and inventory optimization models. It transforms historical sales data and external signals into accurate forecasts, then applies optimization logic to recommend ideal inventory levels across locations, products, and time horizons. The solution includes automated pipelines for data preparation, model training, and inference, along with dashboards and alerts that support real-time decision-making across supply chain and planning teams.

Accelerator : MLOps LaunchPad

MLOps Launchpad is a solution accelerator that helps teams operationalize machine learning on AWS with speed, consistency, and confidence. It provides a reusable framework for deploying, monitoring, and scaling ML models using native AWS services, while embedding automation, governance, and cost visibility into every stage of the lifecycle.

Accelerator : Fraud Detector

UTurn’s Fraud Detector Accelerator ingests transactional and behavioral data, applies anomaly detection and risk scoring models, and triggers automated actions across systems. The solution includes modular pipelines for training and inference, event-driven workflows for alerting and response, and dashboards that give fraud analysts and compliance teams full visibility into patterns and outcomes. 

From Data to Decisions: Fast-Track Your AI Strategy

Opportunities That Matter

Our 4-hour Ideation Workshop is designed to help organizations rapidly uncover high-impact opportunities across data, analytics, machine learning, and emerging AI technologies. Led by senior Data and AI resources and AWS-certified architects, the session blends business discovery with technical insight to identify use cases that align with your goals and infrastructure. Participants gain a clear understanding of how data foundations combined with AI, can drive innovation and efficiency across key domains.

A Clear Path Forward

Through a fast-paced, collaborative format, we deliver a prioritized set of AI opportunities, a readiness snapshot of your current environment, and a tailored blueprint for next steps. Whether you're exploring how you can accelerate your use of advanced tools in the areas of AI, intelligent agents, or advanced analytics, this workshop equips your team with the clarity and direction needed to move forward confidently.

Give agents the context they need to make smarter decisions.

Move From Idea to Impact

Our Rapid Prototyping Service is a four-week engagement that transforms AI ideas into working prototypes through a structured, outcome-driven process. Starting with ideation, we guide teams through solution design, cloud architecture, and hands-on development to validate high-impact use cases. This service is ideal for organizations looking to move quickly from concept to clarity, leveraging AWS-native tools and modern AI capabilities including generative and agentic intelligence.

Build Fast, Build Right

At the heart of this offering is our Realization Factory, a delivery model built to accelerate innovation by combining strategic thinking with technical execution. By the end of the engagement, clients walk away with a functional proof-of-concept, a scalable architecture blueprint, and a clear path to production. It’s not just about building fast, it’s about building right.

Build, deploy, and scale AI with governance and security tailored to your enterprise

Enterprise-Scale AI

AI Production Build Lab through UTurn’s Realization factory is built for teams ready to operationalize AI at scale. We design modular frameworks that support rapid iteration, secure deployment, and long-term governance. From build to deploy, every layer is engineered for adaptability, enabling you to evolve models, pipelines, and integrations without starting over. Our systems are built to scale across environments and teams, with embedded controls for observability, versioning, and rollback.

Security and Governance Built In

Security and compliance are foundational, not optional. We implement identity and access controls, encryption in transit and at rest, and audit-ready logging aligned with compliance needs in your industry, whether you're launching in healthcare, retail, or financial services, our frameworks ensure your AI is not only production-ready but future-ready. You get the velocity to innovate and the structure to govern.

How We Work With You

A Proven Path to Success

We audit and refine your data landscape to ensure it’s clean, curated, and structured for machine learning. We design automated pipelines for scalable pre-processing, feature engineering, and versioning—laying the foundation for reliable, high-quality datasets.

Outcomes:

  • High-quality, ML-ready datasets with traceable lineage
  • Reduced manual effort and error-prone preprocessing
  • Scalable pipelines that support continuous model improvement

Develop and train models in SageMaker Studio using reproducible, modular workflows that balance precision, scalability, and business alignment. Our approach accelerates experimentation while ensuring models are robust, relevant, and ready for production.

Outcomes:

  • High-performing models tailored to your business needs
  • Reproducible training workflows with full experiment tracking
  • Accelerated development cycles through automation and best practices
  • Models that are ready for deployment, monitoring, and continuous improvement

Deploy models to production with SageMaker endpoints, Model Monitor, and CI/CD integrations for seamless delivery and oversight. We ensure performance, reliability, and compliance at every stage so your models continue to learn, adapt, and deliver value.

Outcomes:

  • Reliable, monitored model deployments with automated rollback and alerts
  • Continuous delivery of model improvements with minimal disruption
  • Enterprise-grade MLOps that ensure compliance, scalability, and resilience
  • Measure success through improved model accuracy, reduced operational overhead, and faster time-to-value
  • Clear ROI and efficiency gains across production workflows.