Appinventiv Supercharges AI/ML Innovation and Client Success with AWS SageMaker Premier Partnership

Noida, India – August 14, 2025 – Appinventiv, a global leader in digital engineering and AI innovation, today announced the meaningful progress we are making in the field of digital innovation by being a Premier Partner of AWS SageMaker.

Such collaboration will ensure our mission of bringing unmatched capabilities across the AI/ML lifecycle, allowing our clients to benefit by gaining accelerated time-to-market, a higher level of operational efficiency, and greater competitive advantage.

Our End-to-End AI/ML Excellence Through the Use of AWS SageMaker

Accelerating AI/ML Adoption: We use the unified and fully managed platform in AWS SageMaker to speed up AI/ML adoption for our clients by a drastic margin.

• We can make AI/ML deployment easier by offering an integrated development environment (IDE) such as SageMaker Studio to simplify the process of building, training, and deploying ML models. This will mean that our data scientists and developers can focus on problem-solving and innovation, and reduce the infrastructure burden and the time it takes to deliver solutions.
• We make great use of SageMaker JumpStart as well, which uses pretrained models that one can rapidly customize and deploy, and even Foundation Models of generative AI to rapidly bring powerful AI applications.
• We can cost-efficiently and flexibly scale workloads on SageMakers’ on-demand infrastructure, which directly translates into the agility of experimentation and deployment on behalf of our clients.

Integrating Advanced AI and ML: Our Premier Partnership with AWS SageMaker makes it easy to add advanced AI and ML tools.

• SageMaker enables us to leverage the best in open-source frameworks like TensorFlow, PyTorch, and Apache Spark, which lets our clients use their existing investments while enjoying the full benefits of managed SageMaker services.
• SageMaker facilitates a managed MLflow to track the full history of our experiments and manage model artifacts, and ensure that projects can be reproducible and consistent.
• SageMaker Pipelines enable us to build bespoke ML workflows that can be easily integrated with any other AWS services and unique third-party applications to develop supremely efficient and unique solutions.

Optimization and Automatic Training of Models: We are leading the race in terms of model training optimization and automation by:

• Setting the models with auto mode tuning for achieving a better model performance with minimal manual efforts.
• Scaling up projects by taking advantage of SageMaker distributions with their ability to train distributed models and use SageMaker HyperPod to create stable high-performance computing environments that are necessary to perform complex model development.
• Enhancing training parameters and selects preferred infrastructure using straightforward approaches. This allows us to deliver faster, more cost-efficient, and highly performant training cycles to our clients.

Data Processing and Integration: Through SageMaker Unified Studio and SageMaker Lakehouse, we decompartimentalize our data access to these different data sources, including Amazon S3 and Redshift data, making a unified access.

• We simplify the process of data exploration, preparation, and integration on serverless data integration, and effortlessly link with AWS Glue, Amazon EMR, and Amazon Athena to big data processing.
• We emphasize automated data quality reporting, detection of sensitive data, and lineage tracking using SageMaker Catalog and AWS Glue Data Quality, creating an essential layer of trust and transparency in the data assets of our clients.

Optimization of Model Deployment and Monitoring: We also have expertise in the deployment and persistent evaluation and improvement of models.

• We can deliver this to clients using one-click deployment to fully managed SageMaker endpoints with automatic scaling and load balancing.
• We use SageMaker Model Registry to manage model artifacts and model lifecycle programmatically, thereby significantly reducing the path to production.
• We apply the integrated model monitoring feature in SageMaker to monitor the performance of the model, data, and model drifts, and bias to ensure that the deployed models are accurate and unbiased.
• We also incorporate CI/CD pipelines and best AI observability tools, ensuring continuous improvement and optimal operations.

AI-Powered Insights and Analytics:

With AWS SageMaker, we unlock deeper, AI-powered insights and analytics.

• The integrated SQL analytics capabilities allow us to query structured data directly within SageMaker, boosting productivity. We enhance data discovery through SageMaker Catalog, which uses generative AI to enrich metadata, making data more understandable and usable for business users.
• Our implementation of SageMaker Lakehouse enables real-time data processing, allowing clients to make faster, more informed decisions.
• Furthermore, tools like SageMaker Clarify are integral to our practice, helping us monitor for bias and ensure the fairness and explainability of models, building trustworthy insights.

AI Governance, Compliance, and Security: Governance, compliance, and security are everything.

• We leverage SageMaker end-to-end AI governance capabilities, fine-grained access controls using AWS IAM, data protection by encrypting data, and running in isolated environments.
• Our tailor-built AI solutions adhere to the standard compliance programs such as the HIPAA and the GDPR. We integrate the responsible AI capabilities, such as SageMaker Clarify and Amazon Bedrock Guardrails, to detect bias and ensure fairness, privacy, and accuracy.
• To have improved Governance, Risk and Compliance (GRC), we can interface with state-of-the-art third-party solutions that integrate with SageMaker.

Edge and IoT Integration: For clients with Edge and IoT needs, our partnership is transformative.

• We utilize SageMaker Edge Compiler to optimize ML models for deployment on diverse edge devices, achieving faster inference and reduced latency.
• AWS IoT Greengrass is central to our strategy for deploying and managing AI models across large fleets of edge devices. We implement smart data capture mechanisms via SageMaker Edge Agent for continuous model improvement through real-world data retraining.
• Our automated MLOps pipelines for edge devices, managed by SageMaker Edge Manager, simplify lifecycle management and ensure the security of models on remote devices.

“Our Premier Partnership with AWS SageMaker is not just a badge; it’s a testament to our deep commitment to innovation and client success. We are empowering businesses to harness the full potential of AI and ML, driving real-world impact and future-proofing their operations. This collaboration allows us to provide the scale, flexibility, and advanced capabilities our clients need to lead in the intelligent era,” Said Chirag Bhardwaj, VP of AI at Appinventiv.

About Appinventiv

Appinventiv is a technology consulting and digital solutions development company with over 10 years of experience helping businesses in multiple industries achieve success. Employing an amazing team of professionals of over 1,600 and having a history of more than 3,000 successfully delivered projects, we are one of the fastest-growing companies that focuses on the development of robust and secure AI-powered solutions in 2024. New effective solutions are never going to fall short, and we already have innovative technologies that we can implement, including AI, blockchain, and even IoT. Being trusted partners, we strive to help companies achieve successful digital transformation, make their operations more effective, and provide them with great customer experiences.

About AWS

Amazon Web Services (AWS) is an advanced, secure, scalable cloud platform that is integrated or encompassed by Amazon, and it gives enterprises globally the capacity to innovate, optimize, and grow. AWS was launched in 2006 and offers a large set of services such as computing applications, storage, analytics, database, machine learning, and many others to help organizations to launch, and manage applications.

THE AUTHOR

Appinventiv Technologies