Businesses have massive amounts of messy, unstructured data that takes enormous time to clean and organize manually. Our AI processes 200,000+ records in hours instead of months—with 95%+ accuracy.
Businesses struggle with massive amounts of messy, unstructured data that takes enormous time to clean and organize manually.
Sales records from old platform (CSV files, inconsistent formatting)
Customer notes from support tickets (free-form text)
Inventory logs (mixed date formats, duplicate entries)
Email campaign data (scattered across different tools)
Problem: Need consolidated customer database for analysis and CRM migration
Manual approach would require:
• Data analyst reviewing each entry: 200,000 records
• Estimated time: 3 seconds per record = 600 hours (15 work weeks)
• Cost: $30,000-50,000 (analyst salary + opportunity cost)
• Timeline: 4-6 months with interruptions
100,000+ pages of content or 200,000+ data records
Unfiltered customer data (purchase times, dates, locations, etc.)
Mixed format information (dates, currencies, phone numbers)
Exports to Excel, JSON, CSV, or directly to databases
Why AI is necessary:
Data cleaning requires understanding context, not just automation—our AI comprehends what the data represents and organizes it intelligently.
A comprehensive three-step process that transforms messy data into organized, analysis-ready databases
AI analyzes your data, identifies formats, duplicates, and inconsistencies. Provides comprehensive quality report.
Automatically standardizes dates, deduplicates records, validates data, and normalizes formats.
AI understands data meaning—interprets context, fills gaps, and categorizes intelligently.
Export clean data to Excel, JSON, CSV, or directly import to databases and CRM systems.
AI Analysis:
AI automatically:
Standardizes dates
"3/15/2023", "15-Mar-23", "March 15, 2023" → "2023-03-15"
Deduplicates
Merges records for "John Smith", "J. Smith", "John M Smith" (same email)
Validates data
Flags invalid emails, phone numbers, addresses
Normalizes currencies
"$1,234.56", "1234.56 USD", "1,234.56 dollars" → 1234.56
Categorizes
Groups products, customer types, regions automatically
Fills gaps
Infers missing data from related records when possible
Example of AI's intelligence:
Raw Data Entry:
Customer: "john smith"
Phone: "415 555 0123"
Purchase: "2x blue widget $49ea shipped CA"
Date: "last tuesday"
AI Interprets Context:
Customer Name: John Smith (proper capitalization)
Phone: (415) 555-0123 (standardized format)
Product: Blue Widget
Quantity: 2
Unit Price: $49.00
Total: $98.00
Shipping Location: California, USA
Order Date: 2024-10-29 (calculated from "last Tuesday" + file timestamp)
Our AI goes beyond basic cleaning to deliver intelligent data organization and quality scoring
(missing 8% of optional fields)
(5% flagged for verification)
(date formats standardized)
(12% invalid emails corrected where possible)
Transform data cleaning and organization across industries
Challenge:
10,000 patient files from paper records over 15 years. Handwritten notes, inconsistent abbreviations, mix of metric and imperial measurements.
AI Processing:
Digitizes and standardizes all measurements. Translates medical abbreviations contextually. Links related visits and treatments. Flags incomplete immunization records. Creates searchable, HIPAA-compliant database.
Time: 8 hours vs. 6 months manual entry
Challenge:
Product data from 50 stores (different formats). 25,000 SKUs with inconsistent naming. Some descriptions in Spanish, some in English. Missing product categories for 30% of items.
AI Processing:
Consolidated to single product catalog. Auto-categorized all items. Standardized language to English. Identified $45K in duplicate inventory purchases.
Time: 12 hours vs. 3 months manual work
Challenge:
100,000 insurance claims over 10 years. Claim amounts in various formats. Dates of incident, filing, resolution all mixed. Adjuster notes (unstructured text).
AI Processing:
Standardizes all monetary amounts and dates. Extracts key information from adjuster notes. Categorizes claims by type, severity, outcome. Identifies patterns for fraud detection.
Enabled: Advanced analytics that increased fraud detection by 35%
Challenge:
Data from 15 different ad platforms. Each platform uses different metrics names. Client wants unified dashboard. Historical data going back 3 years.
AI Processing:
Creates master dataset with unified metrics. Builds comparison analysis across platforms. Identifies best-performing channels.
Outcome: Client increased ROI by 42% through data-driven allocation
See the measurable impact our AI data cleaning delivers
Successfully migrated to new CRM in 1 week vs. 6-month projection
Recovered $78K in previously un-billed services
Manual Data Cleaning:
AI Data Cleaning:
Impact: Transform months of tedious manual data work into hours of automated processing. Businesses gain immediate access to clean, structured data enabling better decisions, advanced analytics, and successful system migrations. One client discovered $450K in operational inefficiencies through analysis that was only possible after their data was properly cleaned and organized.
Join companies saving $79,000+ and months of work by automating data cleaning and organization. Process 200,000+ records in hours instead of months.