CleanSmartLabs Products
Intelligent solutions for data you can trust.
Data Cleaning that Actually Works
Upload messy spreadsheets. Get clean, standardized, duplicate-free data back in minutes—not hours.
Duplicate Detection
SmartMatch™ finds what CTRL+F can't.
John Smith and Jon Smyth? Same person. Your database doesn't know that. You do—but you shouldn't have to check every row manually.
SmartMatch uses semantic matching to identify duplicates even when spellings differ, fields are swapped, or someone entered "Johnny" in 2019 and "Jonathan" last week. The AI compares meaning, not just characters. It catches the matches a simple text search would miss entirely.
You review what we find. Decide what to merge. Nothing changes until you say so.
Feature highlights
- Semantic similarity powered by transformer models
- Adjustable matching thresholds—strict or loose, your call
- Cluster view groups related records when duplicates span 3, 4, or 10 entries
- Merge in bulk or review case-by-case
Format Standardization
AutoFormat turns chaos into consistency.
Phone numbers shouldn't come in six formats. Dates shouldn't break every time you open the file in a different program. And email addresses with random capitals look unprofessional in mail merges.
AutoFormat detects the mess and fixes it. We scan your entire dataset, identify inconsistencies, and apply standardized formatting across every row. International phone numbers get proper country codes. Dates convert to your preferred format. Emails clean up automatically.
The tedious stuff? Handled.
Feature highlights
- Phone number normalization for international formats
- Date detection and conversion (even the weird Excel ones)
- Email validation with automatic cleanup
- Address component standardization
- Case correction and whitespace removal
Missing Value Handling
SmartFill™ closes the gaps intelligently.
Missing data happens. Someone skipped a field. An import failed halfway. A column got deleted and nobody noticed for three months.
SmartFill looks at the patterns in your existing data and suggests fills for the blanks. Not random guesses—actual predictions based on what's already there. If every customer from Oregon has the same area code pattern, SmartFill notices. If job titles correlate with departments, it connects those dots.
Every suggestion comes with a confidence score. High confidence? Probably safe to approve in bulk. Lower confidence? Review individually. You're always in control.
Feature highlights
- Statistical and pattern-based predictions
- Context-aware suggestions using related columns
- Confidence scoring for every fill (so you know what to trust)
- Preview everything before applying changes
Anomaly Detection
LogicGuard catches what shouldn't exist.
A customer aged 247. An order total of negative $12,000. A hire date set in 1847. These values slip into datasets more often than anyone admits—and they wreck reports, skew averages, and make dashboards lie to you.
LogicGuard scans for values that break logic or fall way outside normal patterns. Statistical outliers. Impossible combinations. Fields that contradict each other. We flag them before they cause problems downstream.
You decide what to fix, ignore, or investigate further.
Feature highlights
- Statistical outlier detection using multiple methods
- Business rule validation for domain-specific logic
- Cross-field consistency checks (birth date vs. graduation date, etc.)
- Choose to flag issues or apply automatic corrections
Know exactly how clean your data is.
Every dataset gets a Clarity Score from 0 to 100. Think of it as a health check for your spreadsheet.
Upload your file and see where you stand. Watch the score climb as SmartMatch merges duplicates, AutoFormat standardizes fields, SmartFill closes gaps, and LogicGuard catches anomalies. The breakdown shows exactly what's impacting your score—and what you've fixed.
Watch messy data become clean in minutes
Under the Hood
For the folks who want to know how it works, not just that it works.
Security
Encryption in Transit
All data transmitted to and from CleanSmart is encrypted using TLS 1.2. This includes file uploads, API calls, and data exports.
Encryption at Rest
Two layers of encryption protect your data at rest:
- Application-level: API credentials and integration tokens are encrypted using Fernet (AES-256-CBC) before storage
- Platform-level: All database storage runs on Digital Ocean Managed PostgreSQL with AES-256 disk encryption enabled by default
Data Isolation
Customer data is isolated at the database level. Your records, cleaning jobs, and uploaded files are never accessible to other accounts. There is no shared tenancy.
Data Retention
You choose how long CleanSmart keeps your data: 24 hours, 7 days, 30 days, or 90 days. The default is 30 days. You can also delete data manually at any time.
Deletion Receipts
When you delete data, CleanSmart generates a compliance receipt documenting:
- Unique receipt ID
- Timestamp of deletion request and completion
- Itemized count of database records removed by table
- Files and dataframes cleared
- SHA-256 manifest hash for verification
This receipt is your audit trail. Download it, store it, hand it to your compliance team.
AI Training
We do not use your data to train AI models. Your customer records stay yours.
Data Formats
- Input: CSV (all plans), Salesforce, Hubspot, Shopify, Mailchimp, Klaviyo (Pro and Business). Excel and JSON coming soon.
- Output: CSV. Parquet and Excel exports on the roadmap.
- Encoding: Auto-detects UTF-8, Latin-1, Windows-1252
Processing Performance
- CPU-optimized ML inference — no GPU required, runs on standard cloud infrastructure
- Autoscaling containers spin up under load so concurrent users don't wait in line
- 10,000 rows with 18 columns: full pipeline (duplicates, formatting, missing values, anomalies) completes in under 5 minutes on a 2-vCPU production instance
AI Models
- Semantic matching: Sentence Transformers (all-MiniLM-L6-v2) — embeds entire records, not just individual fields
- Fuzzy matching: Normalized Levenshtein distance with phonetic (Soundex) blocking
- Anomaly detection: Isolation Forest, statistical analysis, custom validators
