Transforming Sourcing Value’s manual data processing with AI.
AI-POWERED
DATA PROCESSING
90% REDUCTION
IN MANUAL EFFORT
SEAMLESS
WORKFLOW Integration
Services
Industries
Technologies
About THE Project
Sourcing Value faced major inefficiencies in processing and normalizing data from various suppliers along their supply chain. With Excel files arriving in inconsistent formats each month, their team was spending excessive time manually cleaning, mapping, and integrating data before it could be used for business operations.
The goal was clear—eliminate bottlenecks, reduce human intervention, and automate data transformation with precision. Spiral Scout stepped in with an AI-driven solution powered by Wippy, an agentic AI framework, to streamline data ingestion, validation, and formatting. ingestion, validation, and formatting.
The result? A system that turns weeks of manual work into minutes, freeing up their team to focus on higher-value tasks.
Objectives
- Automate the data processing pipeline, minimizing manual intervention.
- Accurately map and format incoming data from diverse suppliers.
- Reduce operational delays caused by data inconsistencies.
- Seamlessly integrate with existing enterprise tools and workflows.
Challenges
Solutions
Managing Unstructured and Inconsistent Data
Sourcing Value received data from multiple sources in different formats, leading to errors, inefficiencies, and wasted time spent on manual cleanup.
We built an AI-powered processing system for Excel files that automatically recognizes, normalizes, and structures incoming data without requiring human input and gets it into the correct format.
Long Processing Times Delaying Decision-Making
The manual workflow required over a month to process and validate data, slowing down critical business decisions.
Use Agents to Speed up Decision Making
Our automation framework cut review and processing time by 90%, reducing a month of effort for a single person into just minutes for the first execution, after we spent 30 minutes training a data AI Agent for them on a single call with their team.
Risk of Human Error & Data Quality Issues
Manual data handling introduced inconsistencies, created extra work for engineers who would have to reupload files and risked incorrect financial forecasts and supply chain decisions.
Keeping a Human in the Loop
With AI-driven validation and auto-correction, data accuracy improved to over 90%, providing reliable, ready-to-use datasets and we introduced a step where the employee could review all the work for accuracy.
Scalability & Integration with Existing Systems
The previous approach wasn’t scalable, making it difficult to maintain it and adapt as data volume increased.
API and EDI Connectors
We implemented a multi-agent AI system, enabling seamless integration with existing APIs and EDI connectors, ensuring the solution scales effortlessly with business needs.
OUR Project strategy
We knew Wippy.ai could solve this issue but what shaped the project’s success and addressed its key challenges.
AI-Powered Data Processing Engine
Developed an advanced AI model that understands, maps, and restructures data dynamically, significantly reducing errors and inconsistencies.
Multi-Agent AI Automation
Leveraged Wippy’s multi-agent system, allowing different AI models to specialize in data validation, transformation, and workflow execution.
Seamless System Integration
Built custom API and EDI connectors to integrate the automated workflow directly into Sourcing Value’s enterprise systems.
Project results
By transitioning from a labor-intensive data management process to an AI-driven automation system, Sourcing Value dramatically improved operational efficiency, reduced risk, reduced errors, saved an employee’s sanity and positioned itself for scalable growth.
Key Outcomes
- 90% reduction in manual processing time, enabling near-instant data validation.
- 15-minute turnaround for initial execution, compared to over a month previously.
- Up to 90% accuracy in data mapping, ensuring minimal need for manual corrections.
- Automated workflow integration, improving efficiency and decision-making across the organization.
We focused on creating a scalable, automated solution that addressed the client’s most pressing challenges, allowing them to focus on their core operations without worrying about data inconsistencies and processing delays.
Anton Titov
CTO, Co-founder of Spiral Scout
OVERALL SCORE
At Spiral Scout, we believe that when it comes to software development and delivery, it’s time for a change.
5.0
SCHEDULING
On Time / Deadline
5.0
QUALITY
Service & Deliverables
4.0
COST
Value / Within Estimates
5.0
NPS
Willing to Refer
