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DIO® Data Concierge
Find duplicates. See the evidence. Stay in control.
AI-assisted data quality across your CRM, ERP, marketing lists and spreadsheets. Every match arrives with its evidence, and every merge has a person behind it.
Know every customer once.
Name: CRM says Jordan Ellis; ERP export says J. Ellis. Supports the match: Agrees: J. is Jordan.
Load the exports from every system that holds your customers: CRM, ERP, marketing platforms, and the spreadsheet finance keeps on the side. The Concierge maps them, cleans them and compares them, surfacing duplicates that no single system can see on its own.
It shows its working.
Every likely match arrives with the evidence for it and the evidence against it, field by field. A score is never dressed up as a certainty, and when the data can’t decide, the Concierge says so.
It asks before it acts.
Nothing is merged without a person’s approval. Source records are never altered, and every decision is recorded with who made it and the evidence they saw.
Evidence is where the Concierge comes alive. Every match is a case file: the values side by side, what agrees, what conflicts, and what was simply never captured. Your reviewers decide quickly because the reasoning is already on the page.
Queued for side-by-side review, with the evidence against shown first.
Plenty of tools would merge these two on the phone number alone. In our calibration, when the phone matched but the names disagreed, it was the same person only about 1 time in 10. So the Concierge puts the evidence against in front of your reviewer instead of burying it.
Two Sam Taylors. Nothing else in common.
Name: CRM says Sam Taylor; Spreadsheet says Sam Taylor. Supports the match: Identical.
Email: CRM says nothing; Spreadsheet says nothing. No evidence either way: Missing on both sides.
Phone: CRM says nothing; Spreadsheet says 0491 570 110. No evidence either way: Missing on one side.
Company: CRM says Taylor Advisory; Spreadsheet says nothing. No evidence either way: Missing on one side.
City: CRM says nothing; Spreadsheet says Brisbane. No evidence either way: Missing on one side.
CRM
Spreadsheet
Name
Sam Taylor
Identical
Name
Sam Taylor
Email
Not captured
Missing on both sides
Email
Not captured
Phone
Not captured
Missing on one side
Phone
0491 570 110
Company
Taylor Advisory
Missing on one side
Company
Not captured
City
Not captured
Missing on one side
City
Brisbane
Insufficient evidence
Set aside, not guessed. Checked again automatically when new data arrives.
A name on its own can’t settle it, for people or for software. When expert reviewers judged pairs like this, they couldn’t tell 88.5% of the time. The Concierge doesn’t pretend it can: these pairs stay out of your queue, one click away, until a new source gives them real evidence.
One inbox, many people.
Name: CRM says Mei Chen; ERP export says Accounts Payable. Counts against the match: A person and a department.
A shared inbox isn’t a person. Role addresses like accounts@ are recognised for what they are, and every identity is checked for coherence before it becomes a golden record. One team mailbox can’t quietly fold a whole department into one customer.
Same mobile. New employer.
Name: CRM says Robert Nguyen; Marketing list says Bob Nguyen. Weak support: Partly: Bob can be Robert.
People change jobs and keep their mobile. Here the evidence points both ways, so the decision goes to someone who knows the account, with every signal for and against laid out, and the decision recorded alongside the evidence they saw.
“A single, trusted view of every customer and contact, without risky bulk merges. Your team resolves duplicates faster, with the evidence behind every decision and a complete record of who decided what.”
The DIO Data Concierge promise
Real Outcomes: Measured on Real CRM Data, Against Human-Verified Labels
Your Most Careful Data StewardCRM AdministratorDedupe AnalystMigration LeadData AuditorPrivacy OfficerData Steward, CRM Administrator, Dedupe Analyst, Migration Lead, Data Auditor, Privacy Officer
Your Most Careful Data Steward
Patient, forensic, and never in a hurry to merge.
Review Noise, Cut by 78%
Pairs that share nothing but a name are set aside, not queued. On one real CRM the routine review queue fell from 60,475 pairs to 13,320, and every withheld pair is still one click away.
Strong Matches You Can Trust
95% precision on development data and 100% on a held-out test set, measured against human-verified labels. When the evidence isn’t there, it queues the pair for you instead of calling it.
Nothing Merged Without You
Strong is an evidence grade, not a merge permission. Source records are never altered, every decision is recorded, and a reversed decision keeps its full history.
A Phone Number Is Not a Person
Phone matched and the name agreed: the same person 45 times out of 45. Phone matched and the name didn’t: about 1 in 10. The evidence against is shown, never hidden.
Switchboards and Team Inboxes, Caught
Shared numbers and mailboxes are counted by the people behind them, not the rows, so one front-desk line can’t stitch a dozen colleagues into a single customer.
One Golden Record Per Person
Built field by field from the best value in each source, with every value pointing back to the row it came from. Only coherent identities are built; conflicts wait for a person.
Know What Your Data Really Holds
Exports that look complete often aren’t. Profiling shows which columns are empty, misplaced or never captured before you trust a single match.
Find Duplicates. See The Evidence. Stay In Control. Nothing Merged Without You. Knows What It Doesn’t Know. Know Every Customer Once. Find Duplicates. See The Evidence. Stay In Control. Nothing Merged Without You. Knows What It Doesn’t Know. Know Every Customer Once.
Doing The Work Of The Perfect Data Steward.
A Meticulous Digital Concierge.
The Concierge’s Resume
I find the duplicates hiding across your CRM, ERP, marketing lists and spreadsheets, and I show you exactly why I think two records are the same person, or why I can’t tell. I never merge on my own, I never guess when the data can’t decide, and I never forget who decided what. I do the patient, forensic work of a whole data-quality team, so yours can spend its time on the calls that matter.
22K+
Real CRM Records Tested On
1,000+
Automated Safety Tests Passing
Training
Trained on the Hard Cases
Calibrated against human-verified labels from independent reviewers working blind: scores stayed hidden until each reviewer had decided.
Tested on a held-out set it had never seen, so its precision figures aren’t marking its own homework.
Where two reviewers disagreed outright, a person made the ruling. Never a model.
Taught where certainty ends: it measured the pairs expert reviewers couldn’t decide either, and learned to set them aside instead of guessing.
Work Experience
Intake Clerk @Every CSV and Excel export
Maps every column, profiles every field, and flags what was never captured.
Normaliser @Names, emails, phones, companies and places
Makes records comparable without changing a single source value.
Evidence Analyst @Every candidate pair
Weighs what agrees, what conflicts and what’s missing, and grades the match.
Review Coordinator @Your data team
Puts the right pairs in front of the right people, strongest evidence first.
Golden Record Keeper @Your single customer view
Builds one trusted record per person, every value traceable to its source.
Principles
Never merges alone.
A strong match is an evidence grade, not permission. A person approves every merge.
Never guesses.
Pairs the data can’t decide are set aside, flagged and available. Never filled in.
Never touches the originals.
Source records stay exactly as they arrived. The golden record is built beside them.
Never forgets.
Every decision is kept, and a reversed decision keeps its history.
Producing Trusted Records
Across Every System That Holds Your Customers
A trusted record is a customer you can act on without a second look: one person, one record, every value traceable to the system it came from, and a person’s approval behind it.
Smart Intake & Profiling
Load CSV and Excel exports from any system: CRM, ERP, marketing platforms, spreadsheets. Columns are mapped for you to confirm, and the gaps are surfaced before anything is compared. Learn More about Smart Intake & Profiling
Normalisation
Names, emails, phone numbers, companies and places are standardised, so “KESTREL FREIGHT” and “Kestrel Freight Pty Ltd” compare like for like. All of it runs inside the platform; nothing is sent out. Learn More about Normalisation
Evidence-Based Matching
Likely duplicates are found across every source and graded on the evidence, with what speaks for each match and what speaks against it. Learn More about Evidence-Based Matching
Guided Human Review
Uncertain matches go to your reviewers side by side. Pairs the data can’t decide are set aside rather than guessed, so your team spends its time on decisions it can actually make. Learn More about Guided Human Review
Golden Record
Each confirmed identity becomes one trusted record, built field by field from the best source value, with every value traceable to where it came from. Learn More about Golden Record
Contact Validation
Emails, phone numbers and addresses are checked, and shared switchboards and team inboxes are recognised, so a front-desk number never becomes someone’s direct line. Learn More about Contact Validation
Governed AI Assist
An optional second opinion on hard cases. Policy-controlled, checked against your residency rules, and never allowed to merge anything on its own. Learn More about Governed AI Assist
Governed EnrichmentComing next
Fill the gaps from an approved provider, under your rules. Enriched values arrive as evidence that waits for acceptance, and never overwrite what your customers told you. Learn More about Governed Enrichment
It’s time to know every customer once.
Send us one export from your CRM, ERP or a spreadsheet you’ve stopped trusting. We’ll show you what’s really in it: the duplicates, the gaps, and the evidence behind every match.
No bulk merges, no black box, and nothing changes in your systems until your team says so.
