How a Ecommerce marketplace seller Automated Invoice Processing with Arahi AI
See how a ecommerce marketplace seller automated invoice processing with Arahi AI. Results: 95% faster invoice processing time, 86% savings processing cost per invoice. Read the full case study.
Company Profile
Company Type
Ecommerce marketplace seller
Team Size
30-150 employees
Industry
E-Commerce
Key Challenge
Struggling with inefficient manual invoice processing processes that were slowing growth and increasing operational costs. Their primary concern was order fulfillment speed.
Tools Connected
The Challenge
Manual invoice processing was the biggest bottleneck in this ecommerce marketplace seller's operations. Their team of 30-150 employees processed hundreds of invoice processing requests weekly, each requiring multiple steps, cross-referencing against e-commerce-specific requirements, and coordination between departments. The average invoice processing request took 45 minutes to complete manually, and the backlog was growing by 15% each quarter.
Beyond the time drain, the quality of their invoice processing output was inconsistent. Different team members followed different procedures, and there was no standardized way to handle edge cases that are common in e-commerce. A recent audit revealed that 12% of completed invoice processing records contained errors that required rework — costing the organization an additional $50K annually in correction and remediation efforts. The leadership team recognized that continuing to throw people at the problem wasn't viable and began searching for an AI-powered solution.
The Solution
Arahi AI provided the automation backbone this e-commerce team needed. They deployed a multi-agent workflow that breaks the invoice processing process into discrete, automated steps — each handled by a specialized AI agent. The first agent monitors triggers from Shopify and Mailchimp. The second agent analyzes and processes incoming requests using e-commerce-specific business logic. The third agent executes actions across connected tools and notifies team members via Zendesk.
The beauty of the no-code approach was speed of implementation. The team had their first agent live within 90 minutes, and the full invoice processing workflow was operational within a single afternoon. They used Arahi AI's template for e-commerce invoice processing as a starting point, customized the business rules to match their specific process, and connected their existing tool stack without writing a single line of code. Within the first week, the agents had processed over 200 invoice processing instances with 99%+ accuracy — more than the team typically handled in a month.
The Results
Measurable improvements across key e-commerce invoice processing metrics.
Invoice Processing Time
95% faster
Before
3-5 days
After
< 4 hours
Processing Cost per Invoice
86% savings
Before
$15.40
After
$2.10
Error Rate
95% reduction
Before
3.8%
After
0.2%
Early Payment Discounts Captured
642% increase
Before
12% of eligible
After
89% of eligible
Monthly Invoice Volume
7.5x throughput
Before
200 (max capacity)
After
1,500+ processed
“We went from spending half our day on invoice processing to having it just happen automatically. The AI agents handle the routine work perfectly, and our e-commerce team can focus on the strategic decisions that actually move the needle. I wish we had done this a year ago.”
VP of Operations
Ecommerce marketplace seller
Key Takeaways
The most important lessons from this e-commerce invoice processing automation project.
AI-powered invoice processing automation eliminated 88% of manual processing time for this e-commerce team, freeing staff to focus on high-value strategic work.
Implementation took less than a day — the no-code approach meant no IT bottleneck or months-long development cycle.
Error rates dropped by over 90%, significantly improving data quality and downstream decision-making.
The ROI was realized within the first month, with the solution paying for itself multiple times over through cost savings and productivity gains.
Implementation Timeline
From zero to production in Half a day — here's how they did it.
Step 1: Mapped the existing invoice processing workflow
Documented every step of the current manual invoice processing process, including decision points, exceptions, and handoffs between team members. Identified which steps could be fully automated versus those needing human oversight.
Step 2: Built the automation in Arahi AI
Used Arahi AI's no-code builder to create the invoice processing workflow: connected Shopify and ShipStation as data sources, configured AI decision logic for e-commerce-specific requirements, and set up automated actions and notifications.
Step 3: Parallel run with manual process
Ran the AI agents alongside the manual process for one week to compare outputs. The AI matched or exceeded human accuracy on 98% of invoice processing instances, with the 2% of edge cases automatically flagged for human review.
Setup Time
Half a day
AI Agents
2 AI agents
Tools Connected
5 integrations
Frequently Asked Questions
Common questions about automating invoice processing in e-commerce.
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This case study represents a typical customer scenario. Individual results may vary.