Nov 24, 2025
Case Study — Eliminating Manual Data Work With Subterra’s Agentic AI Pipeline
Client Overview
A local Louisiana business relied on a heavily manual workflow for collecting, manipulating, and entering operational data. The process consumed 15–20 hours per employee per cycle, with three employees required to complete the recurring task.
This repetitive workload limited growth and caused internal bottlenecks that stretched across multiple departments.
The Challenge
The client needed a solution that could:
Pull data from multiple internal and external sources
Clean, normalize, and manipulate information to match strict internal formats
Eliminate the human error inherent in manual data entry
Process large batches of data reliably and consistently
Remove the labor burden on three internal employees
Deliver real-time results while maintaining a provable accuracy standard
Their existing process required 60+ labor-hours every cycle, caused delays, and routinely introduced errors.
Subterra’s Solution: A Fully Agentic AI Automation Pipeline
Subterra Technologies engineered a complete agentic AI workflow that automates the entire data lifecycle with no human intervention.
The pipeline:
Monitors and detects new data from predefined sources
Extracts, validates, and interprets incoming information using rule-based and AI-based logic
Cleans, manipulates, and restructures data to align with the client’s internal schemas
Transforms and standardizes the final dataset into the required operational format
Syncs and writes the results into the client’s system with auditability and version control
Runs continuously, fully hands-off
This replaced all manual spreadsheet work while improving consistency and reliability.
Performance & Accuracy
Since deployment, the system has achieved:
99.3% accuracy across the last 300+ automation triggers
Stable processing with zero downtime
Consistent output regardless of data volume or complexity
This accuracy rate significantly outperforms human error rates for comparable tasks and provides a measurable, defensible benchmark of system quality.
Impact & Results
Metric | Before Subterra | After Subterra |
|---|---|---|
Weekly labor hours | 60+ hours across 3 employees | 0 hours (fully automated) |
Accuracy | Human error common | 99.3% accuracy over 300+ consecutive triggers |
Cycle time | Multi-day | Instant |
Workload | Low-value, repetitive tasks | Employees redeployed to high-impact work |
Productivity | Constrained by manual processes | Scalable operations without new hires |
Three employees no longer perform any of the manual data tasks.
Their time is now used for customer-facing or revenue-producing responsibilities.
Business Transformation
The automation didn’t just streamline a workflow—
it fundamentally upgraded how the business operates:
No more backlog or late updates
No weekend “catch-up” data sessions
No risk of transcription errors
Faster decision-making with live-processed data
Leadership can expand operations without scaling labor
A stable automation layer the business can build future workflows on
The new agentic system has become a core part of their operations.
Conclusion
Subterra’s agentic AI automation pipeline delivered:
A 100% elimination of manual data manipulation
Over 60 hours of weekly labor reclaimed
99.3% measurable accuracy across 300+ real triggers
Instant processing instead of multi-day cycles
Greater operational capacity without hiring
This project showcases Subterra’s ability to deliver real operational transformation using intelligent, stable automation.
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