AI ready data for SMEs
Businesses need clean, structured, labelled data before AI can do anything useful. But their documents are full of sensitive client information they can't put into AI tools. We fix that.
Your data. Your models. · Sensitive information never enters the AI layer · Every organisation completely isolated
Dashboard
Last updated 2 minutes ago
Total Documents
1,247
+23 today
Extraction Rate
98.2%
+0.4%
Verified
842
67.5% complete
Avg Confidence
94.1%
+1.2%
Auto-verified
621
73.8%
Human reviewed
221
26.2%
Pending
405
—
Verified Q4_financials.pdf
Uploaded client_contacts.csv
Exported invoice_batch_03
Corrected policy_update.docx
Processing tax_returns_2024.pdf
Why this matters
Clean data
Organised, consistent, structured properly. Every field in the right place, every format standardised. No duplicates, no typos, no guesswork.
Labelled data
Tagged and categorised so AI knows what everything means. Invoice vs receipt. Payment vs refund. Customer vs supplier. Every piece of information identified.
Without both, AI doesn't work. It's like trying to teach someone using a pile of random unsorted notes instead of a proper textbook.
Two ways to get there — both broken
Option 1
Do it manually
Pay staff to go through thousands of documents one by one. Extract information. Organise it. Label it.
Takes months. Costs a fortune. Humans make mistakes.
Average waste
15–25 hours per employee per week
Option 2
Use AI to do it
Fast, cheap, accurate. But your documents contain client names, tax file numbers, bank details.
You can't just upload sensitive client data into ChatGPT.
Result
So you're stuck.
Our solution
Strip PII first, then use AI safely
We scrub all sensitive information — names, TFNs, emails, phone numbers — before your documents ever reach AI. The AI only sees safe, tokenised text.
You get the speed and accuracy of AI without the privacy risk. Fast, cheap, accurate — and safe.
Result
AI speed. Zero exposure.
What we actually do
Before
"inv 23/3 - john - $4500 gst inc - paid?"
"Invoice March 2024 John Smith $4,500 GST"
"INVOICE #445 23-03-24 J.SMITH $4500.00"
Three invoices. Same information. Three completely different formats.
After
Clean. Consistent. Structured. Labelled. Ready for AI.
Your documents, cleaned and structured in minutes
01
Upload
Upload your messy data — PDFs, CSVs, Word docs, text files
02
PII Scrubbing
All PII is stripped on our server. Names, TFNs, emails replaced with safe tokens
03
AI Cleaning
Safe tokenised data sent to our AI. It cleans, structures, and labels it — never sees real PII
04
Remapping
Results mapped back to real values on your server. Demasking happens locally
05
Clean Dataset
Clean labelled dataset returned to your company, ready to use
06
You Delete Everything
Nothing stored permanently. You control what stays and what goes
See the pipeline in action
Raw Input
"Invoice from John Smith, TFN 123 456 789, email john@acme.com, phone 0412 345 678 for $45,000 dated 12/03/2024"
5 PII entities detected
PII Scrubbing
Tokenised Text → AI
"Invoice from PERSON_001, TFN_001, email EMAIL_001, phone PHONE_001 for $45,000 dated DATE_001"
Structured Output
{
"customer": "PERSON_001"
"tfn": "TFN_001"
"email": "EMAIL_001"
"amount": "$45,000"
"confidence": 0.97
}
De-masked Output
{
"customer": "John Smith"
"tfn": "123 456 789"
"email": "john@acme.com"
"amount": "$45,000"
"confidence": 0.97
}
Tokens swapped back locally — never stored
How verification works
Auto-verified — no human review needed
"...balance outstanding as at DATE_001 per attached statement..."
invoice_batch_03.pdf — page 2
Human corrected — saved as training label
"...as per the terms outlined in the attached schedule..."
contract_draft_v3.docx — page 4
Human corrected — saved as training label
Everything you need, nothing you don't
Data Cleaning
- Sensitive information automatically scrubbed before AI sees it
- AI extracts and structures every field
- Confidence score on every extraction
- Low-confidence fields flagged for quick human review
- Every correction improves future accuracy
Drag and drop files here, or browse
PDF, CSV, DOCX, TXT — up to 50MB each
annual_report_2024.pdf
2.4 MB — 24 pages
employee_directory.csv
156 KB — 342 rows
contract_draft_v3.docx
890 KB — 8 pages
Uploaded today
12 files
PII entities found
847
Est. time remaining
~3 min
Export & Ownership
- Download as CSV, JSON, or JSONL
- Choose real values or keep it anonymised
- Your data — you own it completely
- Every organisation’s data completely isolated
- Ready for AI training, analytics, or reporting
1,247 verified records ready to export
Company Chatbot
- Ask questions about your own business data
- Answers sourced from your verified documents only
- Source citations on every answer
- Completely private to your organisation
- No hallucinations — grounded in your actual data
What were our Q4 revenue figures?
Based on the verified Q4 financial reports, total revenue was $2.4M, representing a 12% increase from Q3.
Break that down by client segment
Here's the breakdown by segment:
Join the waitlist
Be the first to get early access when we launch.