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Syngenta
4 months
Farming
USA
Syngenta is a global agritech company focused on sustainable agriculture, delivering innovative solutions to improve crop productivity and resilience. By combining cutting-edge biotechnology, digital platforms, and data-driven insights, Syngenta supports farmers in optimizing yields, managing risks, and utilizing resources efficiently across the globe.
Real-time graph insights with Neo4j
, Neptune
Automated workflow bottleneck detection optimized
Scalable architecture for fast data ingestion
Custom dashboards show resource
dependencies clearly
Graph Database Engineer Backend Developer (Node.js & AWS Lambda)
Data Architect / Solutions Architect
Business Analyst / Operations Specialist
Full Time Contract
Eliminating Data Gaps, Inefficient Reporting, and Weak Customer Understanding
Existing systems lacked performance at scale with interconnected data
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Difficulty in visualizing and analyzing weak points in workflows
Manual processes led to suboptimal asset utilization
To overcome limitations of traditional SQL in analyzing complex relationships, we explored advanced graph technologies offering scalable solutions for enterprise needs. The focus was on automating detection of workflow inefficiencies and dynamically reallocating resources to optimize performance. By leveraging graph databases and intelligent algorithms, we aimed to visualize hidden patterns, improve bottleneck identification, and enable real-time operational adjustments for sustained efficiency and resource optimization across interconnected business processes.
● Can we visualize relationships and patterns that traditional SQL misses?
● What graph technology offers the best scalability for enterprise needs?
● How do we automate detection of inefficiencies in operations?
● Can we dynamically reallocate resources based on graph insights?
Advanced Graph Solutions for Operational Efficiency
We deployed Neo4j to enable relationship-driven data modeling, allowing us to uncover complex interdependencies that traditional databases often miss. To ensure scalability and high availability, AWS Neptune was integrated, supporting horizontal expansion as data volumes grew.
Custom AWS Lambda functions written in Node.js automated critical data processing tasks, reducing manual overhead. We also developed dynamic graph queries designed to detect workflow inefficiencies and identify optimization opportunities in real time.
This architecture empowers teams to proactively address bottlenecks and improve resource allocation, driving operational excellence through intelligent, data-driven insights.
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accelerated processing of complex farming data for faster insights.
reduced operational downtime through optimized resource workflows.
hours saved weekly with AWS Lambda task automation.
boosted overall productivity, enabling smoother farm operations.
DataRopes.ai is a global technology partner which delivers end to end services like data engineering, data analysis, data science and AI & ML
Reviewed on
150 E B St Lbby # 1810
1106 A, 11th floor, Haly Tower,
Sector R DHA Phase 2, Lahore
DataRopes.ai is a global technology partner which delivers end to end services like data engineering, data analysis, data science and AI & ML.
Reviewed on
Address
150 E B St Lbby # 1810
1106 A, 11th floor, Haly Tower,
Sector R DHA Phase 2, Lahore
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