How a leading US-based retailer optimized 7000+ pipelines and enabled 70% faster BI reporting

Supercharged data lake performance, reduced time to insights, and enabled faster decision-making—with 24×7 support and guaranteed SLAs

Business need

A leading US-based retailer specializing in personal care products wanted to accelerate data processing and BI reporting for critical business use cases. With thousands of data pipelines and reports supporting real‑time operations, the retailer needed a scalable, data foundation that could consistently deliver fast, trusted insights. They were looking to enhance the scalability of their Snowflake-based data lake while improving performance, reliability, and cost-efficiencies.

Key business requirements:

Improve data quality, extraction, processing, and orchestration at scale
Eliminate performance bottlenecks and modernize compute intensive batch workloads
Empower enterprise-wide teams with real-time, self-service insights for better decision-making
Ensure on-time delivery of 1200+ MicroStrategy reports to stakeholders with strict SLA adherence
Reduce operational overheads while improving support infrastructure
Leverage automation, agentic AI workflows, and continuously optimization of operations

Enabled 75% faster performance and saved millions of dollars in operational costs with continuous monitoring and optimization

Solution

Impetus provided an end-to-end, intelligent DataOps solution—eliminating performance bottlenecks and cost inefficiencies, while providing always-on support. The solution focused on hydrating the retailer’s data lake with 100% accurate data, continuously optimizing storage and compute, and delivering self-service dashboards for real-time decision intelligence.

Key highlights

Provided 24×7 multi-tier support for 5000+ Snowflake data pipelines, 2000+ Talend pipelines, and 1200+ MicroStrategy reports

Extracted and transformed 400 TB data at high speed, enabling availability of real-time insights to business users

Enabled intelligent orchestration for seamless data loading and processing leveraging Control-M

Identified storage optimization opportunities using specialized AI agents for server operations and health checks

Built scalable Snowflake dashboards to proactively monitor compute and storage usage and costs

Optimized compute-intensive queries to unlock cost efficiencies and accelerate report generation time

Powered intelligent DataOps on Snowflake – optimizing 7000+ pipelines and accelerating generation of 1200+ reports – with 24×7 support

Impact

Impetus’ intelligent DataOps and data engineering excellence helped the retailer build a high performance, scalable, enterprise-grade analytics foundation for mission-critical use cases – including order fulfillment, dynamic pricing, personalized offers, and more. By optimizing performance, cost, and reliability, the client realized a host of powerful business benefits:

Performance gains: 75% faster performance on Snowflake
BI acceleration: 70% faster generation of MicroStrategy reports
End-to-end reliability: 100% SLA adherence for ingestion, processing & report delivery
Cost savings: Massive reduction in compute-related costs
Expanded access to insights: Wider adoption of self-service analytics across the organization

Building an agile brokerage platform and elevating customer experience with agentic AI-driven DataOps

Fortune 200 risk & insurance firm wins 800+ new customers, enables 25,000+ yearly registrations, and lowers cloud costs by 40%

Business need

A Fortune 200 risk and insurance company wanted to drive digital transformation to deliver personalized insurance programs, enhance customer experience, and unlock new revenue streams through advanced analytics.

However, their complex data ecosystem was fragmented across multiple business entities, hindering a unified, real-time view of customers and operations. Moreover, legacy systems struggled to scale for real-time analytics and AI use cases, impacting decision-making and business agility. The organization needed to transition from reactive DataOps to an intelligent, autonomous model that could scale with its global data ambitions, while ensuring reliability, efficiency, and cost control.

Key business requirements:

Unify 1500+ fragmented data feeds into a single source of truth
Create a modern, self-service, governed data platform with advanced analytics capabilities
Power intelligent, data-driven insurance recommendations for customers
Ensure SLA adherence and reliability for business-critical data workloads
Support large-scale, multi-region data workloads with seamless orchestration
Reduce manual effort in monitoring, triage, and remediation workflows
Build a future-proof, AI-ready data foundation for multiple business use cases
Lower spiraling cloud and infrastructure costs

Reduced release time by 75% through continuous AI-driven optimization

Solution

Partnering with the client, Impetus built a secure, scalable unified data platform on AWS, supporting 1,500+ data sources and 1,300+ client integrations across 18+ countries, with real-time ingestion and processing of 100+TB data. This created a governed, AI-ready mesh, empowering teams with 360-degree visibility, smart governance, and advanced analytics at scale. Simultaneously, the platform helped customers identify the most suitable insurance programs for their unique needs.

To enhance operational efficiencies, specialized AI agents were deployed across the client’s AWS ecosystem for continuously monitoring signals, detecting anomalies, performing root-cause analysis, and triggering automated remediation. This reduced manual effort significantly and enabled a massive shift from reactive DataOps to predictive, autonomous, self-healing operations.

Key highlights

Application modernization with zero downtime: Seamlessly migrated 200+ applications from legacy container systems to Kubernetes, managing 60+ clusters

Unified observability & cost intelligence layer: Provided a single pane of glass across performance, resource usage, SLAs, and costs.

Faster releases with DevSecOps: Established native GitOps pipelines integrated with security and quality tools, and enabled single-click CI/CD

AI-powered productivity gains: Integrated GenAI copilots for CI/CD, debugging, PR automation, and more—enhancing developer efficiency and time-to-market

Agentic AI-driven optimization: Leveraged custom AI agents to generate cloud provisioning templates, streamline infra setup, automate right-sizing, and eliminate idle resources.

Intelligent, autonomous operations: Deployed AI agents for anomaly detection, root-cause analysis, incident triage, and self-healing remediation workflows

Self-service provisioning: Delivered a customized portal enabling automated infrastructure provisioning, reducing dependency on niche expertise

Enabled 25,000+ yearly customer contract registrations with agentic DataOps and advanced analytics

Impact

By building a single source of truth and embedding agenticAI-driven DataOpsinto the client’s AWS-based data platform, Impetus transformed the way the company monitors, manages, and optimizes data-driven workflows. They have been able to meet growing customer expectations and unlock new business opportunities, while consistently improving performance, reliability, and cost efficiency.

Business benefits

Massive cost savings: Reduced overall cloud costs by 40% through continuous AI-driven optimization
Faster innovation cycles: Reduced release time by 75%, accelerating delivery of new features and data-driven capabilities
Operational efficiencies: Enabled 90% reduction in resource provisioning time through self-service automation and orchestration
Improved performance: Achieved 99% SLA adherence and 99.8% success rate for data processing jobs, ensuring business continuity
Revenue growth: Enabled 800+ new customer wins and 25,000+ annual client contract registrations with greater personalization
Reduction in MTTR: AI-driven triage and remediation dramatically improved incident resolution speed

Driving 5× Faster Incident Resolution and 3.5× Higher Release Velocity with Agentic AI–Driven DataOps

How a Fortune 100 payment card company supercharged performance, achieved 99.9999% service availability, and elevated the customer experience

Business need

A Fortune 100 payment card company aimed to modernize its data operations and deliver differentiated customer experiences at scale. With data at the core of millions of transactions and interactions, ensuring reliability, speed, and security was critical to sustaining business growth, customer trust, and regulatory compliance.

However, as business demands expanded rapidly, their data operations were becoming increasingly complex and fragmented. Monitoring and troubleshooting remained largely manual, leading to reactive firefighting, delayed issue resolution, and rising operational overheads. Ensuring always-on availability, delivering data-driving insights, and maintaining strict security and compliance controls became challenging.

Key business requirements:

Ensure always-on availability of a mission-critical data platform
Enable real-time visibility across data pipelines, infrastructure, and platform performance
Reduce manual effort in monitoring, triage, and incident resolution
Accelerate onboarding of new data use cases and business teams
Improve speed and accuracy of root cause analysis and remediation
Strengthen enterprise-wide security, governance, and regulatory compliance
Power large-scale platforms and products to support a vast, global customer base
Leverage data and machine learning to deliver personalized customer experiences and drive innovation

Achieved ‘A’ platform health rating, strengthening
resiliency, compliance, and transaction
reliability at scale.

Solution

Partnering with the client, Impetus delivered an end-to-end agentic AI-driven DataOps model, combining deep engineering expertise with intelligent automation. A unified, enterprise-grade data platform was established, enabling seamless ingestion, processing, and consumption of massive volumes of real-time and batch data. This platform supports hundreds of ingestion pipelines, large compute workloads, and petabyte-scale data processing—forming the backbone for enterprise-wide analytics and business applications.

With this foundation, Impetus built a custom, agent-driven intelligence layer that continuously monitors system signals, detects anomalies, and performs automated root cause analysis by analyzing logs at scale. Leveraging specialized agents, automation frameworks, and CI/CD & infrastructure optimization, the payment card company was able to reduce the need for manual intervention and shift from reactive, ticket-driven operations to proactive, intelligent, self-healing DataOps.

Key highlights

Always-on reliability with enterprise-grade SRE

Delivered 24×7 operational support ensuring continuous platform availability
Strengthened system resilience through vulnerability management
Ensured business continuity with robust disaster recovery
Enabled real-time business insights via centralized observability dashboards

Unified, scalable data platform for seamless enterprise-wide access

Built 200+ scalable ingestion pipelines on Google Cloud and optimized these to reduce latency
Performed data analysis, profiling, cleansing, and metadata design across 100+ data sources
Modernized legacy HQL code to standardized, deployment-ready Java-Spark frameworks
Democratized access to business use cases across legacy and modern data environments

Massive-scale infrastructure management and optimization

Managed 3,500+ on-prem virtual servers across a highly distributed ecosystem
Operated 50+ Hadoop clusters, 35+ Kubernetes clusters, Kafka, SQL, and multiple other platforms
Supported 35 TB/day real-time processing, 120 PB batch data, ~30K daily ingestions, and 1.2B monthly requests
Led architecture design and threat modeling for enterprise applications

Agentic AI and GenAI-driven operational intelligence

Implemented specialized agents and bots for vulnerability management, incident categorization and root cause analysis
Leveraged AI to detect unused resources and optimize infrastructure utilization
Integrated a Slack-based chatbot with ServiceNow for efficient issue analysis, query handling, and real-time updates

Automation-led efficiency and resilience at scale

Reduced manual effort by 50% using Ansible and Shell scripting
Automated incident and alert generation via ServiceNow and Slack
Enabled single-click CI/CD deployments using Jenkins, SonarQube, and XL Release

End-to-end governance with enterprise-grade security

Empowered organization-wide users with a unified view of business, technical, and operational data
Implemented event- and attribute-level access controls
Ensured secure data transmission through powerful encryption

Eliminated 2,500+ monthly failures through AI-driven remediation, improving the customer experience and reducing risk

Impact

Impetus helped the payment card company transition from traditional, reactive DataOps to an intelligent, autonomous, cost-efficient model that could drive operational excellence at massive scale. This foundational shift empowered business users across service lines—enhancing analytics-led decision-making and enabling personalization of customer experiences. Simultaneously the engagement reduced overall risk, strengthening compliance and governance.

Business benefits

Always-on reliability: Achieved 99.99% availability, ensuring business continuity
Faster incident resolution: Enabled 400% faster incident resolution through AI-driven triage and RCA
Operational efficiency: Reduced manual effort by 50%, enabling teams to focus on innovation
Improved performance: Enabled 50%+ faster data processing and resource utilization
Faster time-to-market: Accelerated release deployment frequency by 250% per month
Stronger security posture: Achieved 99% security compliance, strengthening adherence to regulatory standards
SLA excellence: Delivered 100% SLA adherence for infrastructure provisioning and CI/CD operations
Agile delivery maturity: Enabled 100% SAFe-aligned teams and delivery processes, improving consistency and execution at scale

Accelerated cloud migration and enabled 130+ AI business use cases for a Fortune 100 Airline

Modernization to an AWS-based data lake enabled 50% annual cost savings and enterprise-wide
ML & GenAI adoption

Business need

A Fortune 100 airline leveraged a legacy Teradata data warehouse to manage enterprise data, resulting in manual-intensive processes and spiralling operational costs. Troubleshooting was time-consuming and high failure rate significantly impacted operational SLAs. Additionally, legacy infrastructure made it challenging to build, deploy, and scale ML and GenAI use cases. The airline wanted to move to a scalable, reliable cloud architecture to enhance operational efficiencies, lower costs, and power AI-driven innovation.

Key business requirements:

Modernize Teradata workflows to AWS, optimizing large-scale pipelines and infrastructure
Ensure high data quality for downstream use cases with 24×7, end-to-end observability
Simplify data operations, reduce manual effort, and lower operational costs
Improve passenger experience with better platform reliability and deeper data-driven personalization
Leverage ML & AI workflows to power chatbots, streamline baggage tracking, and enhance passport OCR, coupon-based offers, etc.

Delivered a unified, agentic DataOps-driven platform, enabling enterprise‑scale ML and GenAI innovation for 3500+ users

Solution

Impetus established a reliable, scalable data foundation by modernizing the airline’s legacy data warehouse to a cloud-native data lake architecture leveraging AWS Glue, Amazon MWAA, Amazon Redshift, and Palantir Foundry.

Building on this foundation, the team implemented a unified AI/ML platform, which was leveraged by 3500+ users to host and manage 150+ business-critical applications. The focus was on controlling costs,

From CI/CD automation to proactive monitoring, the engagement enabled seamless automation, cost optimization, and operational excellence.

Solution highlights

Seamless cloud orchestration: Migrated 100+ jobs to Harness, accelerated infrastructure deployment on AWS via IaC templates, while optimizing CI/CD pipelines.

Automation and agentic AI: Optimized queries using SQL Ninja, accelerating troubleshooting with a specialized RCA bot, and enabled AI‑based review of MWAA DAGs and logs to prevent failures.

End-to-end observability: Implemented a best-in-class observability platform for 24×7 monitoring and prevention of data quality issues.

Best-in-class support & reliability: Delivered round‑the‑clock support for ML operations with proactive monitoring, incident and DR readiness.

Governed MLOps: Established robust governance across IAM, AWS services, and GitHub, handling troubleshooting across applications and pipelines.

Enterprise-grade security: Addressed 5000+ vulnerabilities across platforms and applications, and managed security compliance via Wiz and Veracode.

Continuous optimization: Deployed proven optimization techniques to consistently control and reduce cloud spend.

Accelerated releases, with <10% change failure rate and 30% faster debugging, while reducing cloud spend by 25%

Impact

Impetus helped the airline accelerate their cloud modernization journey through agentic AI-driven DataOps, enabling deployment of ML and GenAI workflows at scale. This in turn empowered enterprise-wide users to innovate and unlock unmatched efficiencies across multiple use cases.

Business benefits

Lower platform costs: 50% cost savings annually with data pipeline and platform optimization
Faster issue resolution: 30% fast debugging for MWAA-based data pipelines
Safer deployments: <10% change failure rate on Harness for AWS
Higher AI adoption: 3,500+ AI-driven user requests served across the enterprise in 2025
Improved risk management: 5,000+ crucial security vulnerabilities addressed
Lower cloud spend: 25% AWS cloud cost savings achieved through continuous optimization

Independent Benchmark Report: Automated Database Migration Tools

The Imperative

Business need

Enabled 75% faster performance and saved millions of dollars in operational costs with continuous monitoring and optimization

Solution

Powered intelligent DataOps on Snowflake – optimizing 7000+ pipelines and accelerating generation of 1200+ reports – with 24×7 support

Impact

Business need

Reduced release time by 75% through continuous AI-driven optimization

Solution

Enabled 25,000+ yearly customer contract registrations with agentic DataOps and advanced analytics

Impact

Business need

Achieved ‘A’ platform health rating, strengthening resiliency, compliance, and transaction reliability at scale.

Solution

Eliminated 2,500+ monthly failures through AI-driven remediation, improving the customer experience and reducing risk

Impact

Business need

Delivered a unified, agentic DataOps-driven platform, enabling enterprise‑scale ML and GenAI innovation for 3500+ users

Solution

Accelerated releases, with <10% change failure rate and 30% faster debugging, while reducing cloud spend by 25%

Impact

Achieved ‘A’ platform health rating, strengthening
resiliency, compliance, and transaction
reliability at scale.