Here's a number that should terrify you: if your team manually processes 10,000 invoices, they will make between 100 and 400 errors. A computer? Between 1 and 4 errors. Same task. 100 times fewer mistakes.
Right now, you're paying smart, expensive people to do the digital equivalent of digging ditches with spoons. They open PDFs, squint at numbers, type them into spreadsheets, double-check (and still miss things), and repeat this soul-crushing process hundreds of times a week.
The average company wastes $12.9 billion on poor data quality caused by manual entry. Every typo, every decimal point in the wrong place, every invoice number transposed costs you real money.
What if data just... moved itself?
Let's do some simple, painful math together.
Manual data entry has a 1% to 5% error rate. That sounds small until you realize what it actually means. If your invoice processor handles 20 data points per invoice (vendor name, invoice number, date, line items, amounts, tax, etc.), then with a 1% error rate, statistically every 5th invoice contains at least one error.
But here's where it gets worse. Most companies use a two-phase system: someone writes it down first, then someone else types it in. Now you have 40 data points instead of 20. With the same 1% error rate, 40% of your processed documents contain errors.
Let that sink in. Almost half.
A manual data entry clerk processes about 80 documents per day. That's roughly 5 minutes per invoice. Sounds reasonable, right?
A document automation system processes the same invoice in 3 seconds. Not 3 minutes. 3 seconds.
Manual invoice processing costs between $12 and $35 per invoice. Automated processing? Around $5. That's a 60-80% cost reduction per document.
If you process 10,000 invoices annually, you're spending $120,000 to $350,000 when you could be spending $50,000. You're literally setting $70,000 to $300,000 on fire every single year.
Companies that implement document automation see 200-300% ROI in the first year. One financial services company saved $2.9 million annually just by cutting their manual document team in half.
For every 10,000 documents processed, humans make 100-400 errors while automated systems make 1-4 errors. You're not just a little less accurate. You're catastrophically less accurate.
If you use the common two-phase manual entry system (write it down, then type it in), statistically 40% of your records have at least one error. Almost half your data is wrong.
Poor data quality costs the average organization $12.9 billion per year. Every typo cascades into wrong reports, bad decisions, and lost opportunities.
We believe data should move itself. If a digital invoice arrives in an email, no human should have to open it, read it, and type the numbers into accounting software. That's a waste of human intelligence.
The moment a document arrives (email attachment, scanned PDF, photo from a phone), our AI instantly scans it. It doesn't matter if it's a messy handwritten receipt or a perfectly formatted invoice. It reads like a human, but processes like a machine.
"Optical Character Recognition (OCR) and Intelligent Character Recognition (ICR) with 99% accuracy on structured documents and 85-90% on messy, unstructured documents."
The system doesn't just see random characters. It understands context. It knows the difference between an invoice number and a phone number. It recognizes vendor names, dates, line items, and totals.
"Companies using intelligent document processing cut their processing time by 60-70%. What used to take 12 days now takes under 3 days."
Before entering any data, the system cross-checks it against your existing records. Does this vendor exist in your system? Does this price match the purchase order? Is this date reasonable?
"Automated systems achieve 99.99% accuracy. Human data entry? 96-99% at best. That 3-4% difference is thousands of errors per year."
The system enters the data directly into your ERP, CRM, accounting software, or database. No copy-paste. No re-typing. No human bottleneck.
"One engineering firm cut their RFP response time from 3 weeks to 1 week and increased their processing capacity by 400%."
Every document becomes instantly searchable data. "Find all contracts with Vendor X that mention price escalation clauses signed after March 2023" returns results in seconds, not hours of manual digging.
"No more "Where is that invoice from 2019?" moments. No more digging through filing cabinets or messy folder structures."
| Metric | Manual Data Entry Clerk | Kodekx Document AI |
|---|---|---|
| Speed Per Document | 5 minutes (on a good day) | 3 seconds (every time) |
| Daily Capacity | 80 documents (if they're fast) | Unlimited (seriously, unlimited) |
| Error Rate | 1-5% (industry standard) | <0.1% (near-perfect) |
| Cost Per Invoice | $12-$35 (salary + benefits + overhead) | ~$5 (fraction of manual cost) |
| Availability | 8 hours/day, Mon-Fri (minus breaks, sick days, vacations) | 24/7/365 (never sleeps, never calls in sick) |
| Accuracy on 10,000 Documents | 100-400 errors | 1-4 errors |
| Processing Time for 10,000 Invoices | 833 hours (20+ weeks of full-time work) | 8.3 hours (one business day) |
| Annual Cost for 10,000 Documents | $120,000-$350,000 | ~$50,000 |
Real-Time Everything
The Pain: End-of-month reporting is always late because you're stuck waiting for data entry to catch up. Your financial visibility is always 2-3 weeks behind reality.
The Gain: Documents are processed the second they arrive. Your dashboards update in real-time. Your financial visibility is always current.
The Proof: Companies report 60% improvement in cash flow visibility. One company cut invoice processing from 12 days to under 3 days.
No More Typo Nightmares
The Pain: A simple typo in an invoice number or a misplaced decimal point cascades into accounting chaos. Reconciliation is a monthly nightmare.
The Gain: The system doesn't make typos. Ever. It copies data exactly as it appears with 99.99% accuracy. Suspicious documents are auto-flagged.
The Proof: Organizations report a 67% decrease in document errors and a 90% reduction in error-related rework. One company avoided $2.9M in error-correction costs.
Find Anything in Seconds
The Pain: "Where is that contract from 2019 with the price escalation clause?" leads to hours of digging through filing cabinets.
The Gain: Every document becomes searchable, structured data. Search across millions of files by vendor, date, amount, clauses — results in seconds.
The Proof: Document retrieval times drop by 90%. Compliance audits that used to take weeks now take days.
Yes, you save 60-80% on processing costs. Yes, you eliminate 100x more errors. But here's what the spreadsheets don't capture:
Nobody dreams of becoming a data entry specialist. Your smart employees hate doing robotic work. Studies show 81% of workers say automation gives them more time for valuable tasks.
"One pharmaceutical company automated 72 document processes and saved 11,000 hours."
While your competitors are waiting for their manual processing to catch up, you're making decisions based on real-time data.
"One engineering firm increased their RFP processing capacity by 400% and won 40% more proposals."
Want to double your business? With manual processing, that means hiring, training, and managing twice as many people. With automation, doubling your volume costs you almost nothing.
"One company automated 87% of their order lines (1.9M total). They went from 57 to 7 full-time employees."
The Bottom Line: Companies implementing document automation see 200-300% ROI in the first year. Payback period? Less than 6 months. After that, it's pure profit.
Right now, your most valuable business information is trapped in static files. Invoices. Contracts. Receipts. Purchase orders. Every single one contains data you need to run your business, but that data is locked behind manual labor.
Here's the ugly reality:
The companies eating your lunch? They automated this 2 years ago. While your team is typing invoices, their team is analyzing markets, closing deals, and building products.
You have smart, expensive people doing robot work. That's not a staffing problem. That's a leadership problem.
70% of data entry tasks can be automated with current technology. The only question is: how much longer can you afford to wait?
Here's what's happening right now, while you're reading this:
Your competitor just processed 100 invoices in the time it took your team to process 3.
They're making decisions on real-time data while you're working off last week's numbers.
They're winning the bid because they responded in 3 days while you need 3 weeks.
After 6 months, every dollar you save is profit you wouldn't have had. Every hour your team isn't doing data entry is an hour they're growing your business.
The question isn't whether automation works. The data proves it works. The question is: can you afford to keep losing to competitors who figured this out before you did?