Case Studies
How our automation projects have worked in practice, with the numbers behind each one.
Discuss a Similar ProjectAutomating Purchase Invoice Matching
From 4 operators to 1, with 90-95% automation
The Challenge
A logistics client, dealing with hundreds of purchase invoices weekly, was constrained by a manual, time-consuming invoice-matching process that required multiple operators and presented frequent errors.
Our Solution
Custom automation solution using Microsoft Power Automate, AI Builder, and SQL Server
Results Achieved
- Reduced staff requirements from 4 to 1
- Processing time cut to approximately 10 minutes per 100 invoices
- 90-95% of invoices processed automatically
- Minimized errors and clear flagging of exceptions
Before & After Metrics
Before Implementation
- Operators:4
- Time:Hours per 100 invoices
- Automation Rate:0%
- Error Rate:Frequent duplications, incorrect values
After Implementation
- Operators:1
- Time:10 minutes per 100 invoices
- Automation Rate:90-95%
- Error Rate:Minimized, flagged clearly
"The automation has become an essential part of our operations, yielding substantial time and cost savings. It's hard to imagine our workflows without it."
Lead Research & Qualification Automation
Research time per lead cut from 3-4 hours to 15 minutes
The Challenge
A B2B sales team was spending 3-4 hours manually researching each new lead that completed their contact form, delaying follow-up and reducing conversion rates. The research process was inconsistent, with different team members gathering different information.
Our Solution
End-to-end automated lead research system that triggers when a contact form is submitted, gathering comprehensive company intelligence from multiple sources and delivering a complete sales briefing. Designed for minimal disruption to existing workflows with a phased implementation plan
Results Achieved
- Reduced research time from 3-4 hours to just 15 minutes per lead
- Increased lead response speed by 95%
- Conversion rates up 37% because reps had better context before the call
- Standardised intelligence gathering across all leads
- Created a searchable knowledge base of prospect intelligence
- Sales team spends time selling instead of researching
Before & After Metrics
Before Implementation
- Research Time:3-4 hours per lead
- Response Time:24-48 hours
- Data Consistency:Highly variable
- Knowledge Management:Scattered across emails and notes
- Team Notification:Manual process
After Implementation
- Research Time:15 minutes (fully automated)
- Response Time:Under 2 hours
- Data Consistency:Standardised format for all leads
- Knowledge Management:Centralised, searchable knowledge base
- Team Notification:Instant Slack notifications
"The automated lead research system has transformed our sales process. Our team now enters every conversation armed with deep insights about the prospect's business, challenges, and industry trends. It's like having a research department working 24/7."
AI-Powered Inventory Optimisation
23% lower inventory costs, 64% fewer stockouts
The Challenge
A retail business with multiple locations was struggling with inventory management, resulting in overstocking of slow-moving items and stockouts of popular products.
Our Solution
Predictive inventory management system using historical sales data, seasonal trends, and external factors to optimise stock levels
Results Achieved
- Reduced overall inventory costs by 23%
- Decreased stockouts by 64%
- Better cash flow from smarter purchasing cycles
- Fewer missed sales from out-of-stock products
Before & After Metrics
Before Implementation
- Inventory Costs:High carrying costs
- Stockouts:Frequent (8-10% of SKUs)
- Ordering:Manual, intuition-based
- Turnover:Low for many items
After Implementation
- Inventory Costs:Reduced by 23%
- Stockouts:Rare (3% of SKUs)
- Ordering:Automated, data-driven
- Turnover:Optimised across product range
"The AI inventory system pays for itself many times over. We're carrying less stock but have better availability - it's transformed our retail operations."
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