Data solutions for an AI-powered service intelligence platform trusted by Ciena and Emerson
A fast-growing platform that brings agentic AI to frontline service operations at enterprises like Ciena and Emerson engages AgileEngine as a strategic engineering partner. Our experts helped the client close expertise gaps in areas like orchestration and visualization while strengthening the overall data foundation of the company’s key product.
Industries
Artificial intelligence, Customer service, Enterprise software, SaaS, B2B
Services
Data engineering, Architecture, System optimization
Solutions
AI, Data pipeline, Data aggregation, Data warehouse, Business intelligence, Dashboard, Enterprise application
Technologies
Python, Apache Airflow, Apache Spark, Apache Superset
AI tools that powered our workflow
Copilot, Cursor, ChatGPT
Outcomes
and highlights
- Up to 46% faster resolutions delivered by the platform to enterprises, such as Ciena, NCR Atleos, Terumo, and more
- Faster access to operational insights achieved by eliminating Superset dashboard timeouts
- Development velocity and maintainability improvements thanks to reusable standards for Airflow DAG creation introduced by AgileEngine
Solutions overview
Data engineering foundations for AI-driven service resolution
AgileEngine facilitates the client’s core development efforts focused on the data infrastructure build-out and optimization. Our expertise and deliverables became integral to the data pipelines underpinning AI functionality, including first-time fix preservation, troubleshooting, and predictive recommendations. Beyond execution, we introduced best practices, standardized workflows, and knowledge sharing, contributing to a more effective data engineering process across the client’s organization.
Key deliverables
- Data pipelines set-up and maintenance
- Data cleaning and transformation
- Optimization of queries
- Integrations management
- Deployment support
- Ownership over the development of Airflow and Superset solutions
- Knowledge sharing sessions on creating new Airflow DAGs and setting standards, provided by our engineers for the client’s internal team
Technologies
Python, Apache Airflow, Apache Spark
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