Established in 2014, our company operates at the convergence of AI, cloud computing, data, and product engineering, providing comprehensive solutions from strategy formulation to implementation. With a team of over 285 engineers and extensive expertise in production-ready systems, we assist businesses in advancing from proofs of concept to large-scale operations, modernizing outdated infrastructure, developing cloud-native platforms, and integrating AI into essential workflows for tangible results. Our skills cover critical areas of technology, including: 🔸 AI readiness through modern data architectures, pipelines, and production machine learning/generative AI 🔸 AWS-native architectures implementing microservices, serverless computing, and infrastructure as code 🔸 Cloud-native applications with scalable backend systems and an API-first approach 🔸 Specialized expertise in AI/ML, data, cloud (DevOps/SRE), and full-stack development With over ten years of experience in providing data and AI solutions, Applify has established a strong partnership with the AWS ecosystem, achieving the status of an AWS Advanced Tier Services Partner in 2024. Supported by more than 100 AWS certifications and over 300 successful AWS project deployments, we possess proven skills in designing, implementing, and scaling cloud-native systems in accordance with AWS best practices. Notable results we have achieved include: ✦ A 60% reduction in cloud operation costs through automation in DevOps ✦ Over $2 million in cost savings achieved through AI-driven optimization ✦ An 80% decrease in system downtime via predictive, AI-enhanced monitoring ✦ A 40% increase in data accessibility through governed data architectures Recognized by outlets such as India Today, Business Standard, MSN, ANI, and Morningstar, Applify combines strategic planning with execution to create scalable, impactful systems that enhance efficiency and drive innovation. Discover our solution-focused accelerators “LakeStack, LaunchX, and FieldQ,” which are designed to standardize data pipelines and improve execution reliability in operational systems with high interdependencies.