Empowering Enterprises ThroughData and Digital Modernization
ReKnew's pre-built accelerators enable rapid delivery of high-impact use cases - risk, compliance, fraud detection, complaint resolution, etc. - while modernizing data infrastructure to ensure secure, reliable AI adoption.
Built by Practitioners, Designed for Scale
Our team consists of former enterprise data leaders with decades of experience in building modern,
cloud-native data platforms. We bring deep expertise in:
Modernization Roadmaps
Strategic planning to align data investments with business outcomes.
Cloud-Native Architecture
Designing and implementing scalable, secure, and future-ready data ecosystems.
ROI-Focused Delivery
Measurable impact through streamlined implementation and automation.
Bridging the Gap forScalable AI Adoption
ReKnew's Context Engineering™ approach helps enterprises adopt AI by closing the gaps across data, cloud,
workflows, and talent. ReKnew helps business groups mitigate "Context Chasm".
Context Engineering™: A Smarter Approach
Our proprietary Context Engineering™ framework enables organizations to create clear, actionable AI adoption roadmaps. It aligns data with business context - ensuring AI is not just a technology investment, but a catalyst for real-world outcomes.
AI Adoption: Safe, Strategic, Impact-Driven
With our "Business Value as the Driver" approach and "Safe from the Start" architectural principles, we help enterprises deploy AI responsibly - turning innovation into a force for good.
Decades of Experience in Global Execution.
Our team brings decades of proven success in delivering data, machine learning, analytics, and AI solutions. Backed by a fast-moving global delivery model, we prepare both business and IT groups for the demands of an AI-native world.
Enhancing Enterprise Intelligence ThroughWorkflow Automation
ReKnew helps enterprises unlock new levels of intelligence by automating business workflows across the organization. From data to DevOps, our solutions streamline operations and empower faster, smarter decisions.
S
Quad™ Suite: Accelerators for Agentic Transformation
Our proprietary S Quad™ suite of accelerators enables rapid design and deployment of intelligent agents - seamlessly integrating them across your enterprise's Data, Application, DevOps, and ERP layers.
From Pilots to Platform Adoption
Many organizations experience isolated automation wins. Our structured delivery model helps both business and IT teams evolve from these one-off successes to fully operational agentic platforms that scale across functions.
Built for the Business Groups
ReKnew's pre-built knowledge graphs are designed to support data-driven decision-making for leaders across the enterprise - including CFOs, CMOs, CROs, and CIOs - accelerating insights and improving outcomes.
Real Use Cases. Measurable Value. Fast Delivery.
We bring an ever-expanding portfolio of pre-built use cases across:
With implementation timelines measured in weeks, our solutions deliver real business value fast.
Built byFounderswith Decades of
Experience From Large Enterprises
How WePartner
ReKnew's services are designed to partner with enterprises in modernizing data platforms, accelerating AI adoption, and implementing intelligent automation.
Business Workflow Automation
Acceleration from POC to productionized intelligent agentic systems that automate, integrate, and optimize complex business processes enterprise-wide.
Modernizing Enterprise Data Assets
Modernize Data, BI and Analytics platforms to be Cloud Native, with the right grain and available at scale
Data Governance and Context
Safety from the start protocols helps deliver highly governed data which provides comprehensive context of the data. Contextualized data enables business groups make decisions confidently.
Success Stories
From Reports toReal-TimeEngagement
Our team enabled a large global financial institution to modernize its data infrastructure and analytics, transitioning from traditional reporting to real-time customer engagement across omnichannel digital platforms.
Key Actions:
- Created strategic backlog of operational and analytical data and back-wide real-time event taxonomy
- Isolated traditional needs from modern needs to allow two-speed architecture
- Modernized stack to integrate fast and slow data, data services (APIs), and serving layers
Outcomes:
- Enabled data utilization for personalized customer engagement across digital channels
- Developed modern data infrastructure using Hadoop and Kafka
- Established a new Agile DataOps function
From Siloed toScaledImpact
Partnered with a large national financial institution to redesign its AI engagement and operating model, transitioning from siloed efforts to a scalable hub-and-spoke structure that resulted in a 2.5x increase in AI-driven value.
Key Actions:
- Delivered AI strategy and roadmap, business opportunity plans, and a data literacy program
- Conducted talent and operating model assessments
- Redesigned operating model to a hub-and-spoke model
- Established new metrics, goals, platforms, and a cloud analytics roadmap
Outcomes:
- Scaled impact 2.5x (from $20MM to $60MM in new annual value)
- Business-aligned AI pods sized to investments and roadmap
- Hub-and-spoke model that ensures consistency, collaboration, and cohesion
Cut Costs. Elevate Experience.DelightCustomers.
We optimized a large national financial institution's customer service division by deploying AI-powered models across digital channels, ultimately reducing operational expenses, enhancing efficiency, and increasing client satisfaction.
Main Actions
- Deployed AI models to identify customer friction
- Predict in-the-moment customer needs
- Optimize agent routing
- Deliver dynamic digital presentations
Outcomes
- Reduced operational expenses with predictive analytics
- Increased effectiveness of self-service and agent support through AI-driven insights
- Enhanced customer satisfaction with more personalized and proactive experiences
