Field-level checks, not record-level
Accuracy is measured per field, not per row. A record where 9 of 10 fields are right isn't a 90% pass — it's a record with a known bad field, flagged as such.
Services — data analysis
Analysis is only as good as the data under it. So we verify every field.
Most data arrives with no way to check it. Crawlify verifies at the field level, then ships the proof with the record: the source URL you can open, the timestamp it was captured, and the verifier ID that checked it. Our standard is 99.5% field-level accuracy. It's the only published field-level accuracy standard in this category, and it's the layer everything else depends on.
Verified Record
Every field is verified at the source.
Acme Pro Headphones
example.com/products/acme-pro
FieldValueVerification
- Product NameAcme Pro HeadphonesVerified
- Price$39.99Verified
- Stock18Verified
- CategoryHeadphonesVerified
- StatusActiveVerified
Accuracy Claim
No Evidence99.5%Field-level accuracy
- No record attached
- No source attached
- No proof to verify
VS
Verification Receipt
99.5% Field AccuracyAcme Pro Headphones
example.com/products/acme-pro
FieldValueVerification
- Product NameAcme Pro HeadphonesVerified
- Price$39.99Verified
- Stock18Verified
- CategoryHeadphonesVerified
Positioning
“Accurate data” is a claim. Verification is a receipt.
Every data vendor says their data is accurate. Almost none of them will tell you what that means, at what level it's measured, or how you'd check it yourself. Accuracy stated as a percentage on a marketing page, with no per-record evidence behind it, is a claim you're being asked to take on faith. That's the layer between raw extraction and a decision you're willing to defend in a meeting, a board memo, or an audit. Extraction gets you the data. Verification is what makes it worth acting on.
Verification is different. It means each field on each record was checked, and the record carries the evidence with it: where it came from, when it was captured, what checked it, and how confident that check was. You don't have to trust the number on our website. You can open the source URL on any record we deliver and see for yourself.
Capability
Verification is specific, or it's nothing.
Verified only means something if you can say what was checked. Here's what happens to every record before it reaches you.
Capture timestamp
When the value was true. Data without a timestamp is data of unknown age — a different problem from data that's wrong.
Human confirmation on judgment calls
Where an automated check can't confirm a value, a person does. Verification today is tooling plus human confirmation, and the system absorbs more of it over time as it learns your sources.
Source capture
Every record carries the URL it came from, so any field can be traced back and confirmed by you, not just by us.
Confidence scoring
Every automated classification carries a confidence score. High-confidence records pass through; low-confidence records route to human review rather than shipping unchecked.
Flagged, never guessed
Anything that can't be verified is marked unconfirmed. It is never filled in with a best guess or passed off as verified. A smaller trustworthy file beats a larger uncertain one.
Provenance
Note The Fourth Field.
It couldn’t be corroborated, so it ships marked unconfirmed rather than guessed. That’s what verification means in practice: you always know which fields to trust and which to check.
Talk to usverified_record.json
{
"record_id": "REC-552817",
"fields": {
"company_name": { "value": "Example Manufacturing Ltd.", "verified": true, "confidence": 0.998 },
"director_name": { "value": "A. Sharma", "verified": true, "confidence": 0.994 },
"registered_status": { "value": "active", "verified": true, "confidence": 0.999 },
"email": { "value": "unconfirmed", "verified": false, "reason": "catch_all_domain_not_corroborated" }
},
"field_accuracy": 0.995,
"captured_at": "2026-08-24T09:14:02Z",
"verifier_id": "hv-6712",
"verification_method": "automated_checks_plus_human_confirmation",
"source_url": "https://example-registry.gov/company/8841027"
}How It Works
A managed service, not a tool you rent by the request.
- 01
Scope
You bring the sources and the target schema. We confirm what's public, what's feasible, and the cadence.
- 02
Deliver
Project-based verified pulls into your stack.
- 03
Graduate to feeds
As volume and cadence grow, one-time pulls become continuous feeds. Projects first, feeds as you scale.
Fit
Where verified data fits versus the alternatives.
Three honest alternatives: take the raw feed as-is, buy a big enrichment database, or check it yourself.
| Stage | Raw scraped dataas-delivered feed | Data enrichment toolsZoomInfo, Apollo, Clearbit | In-house QAyour own team checks | Crawlify |
|---|---|---|---|---|
| Database breadth / coverage | Varies | core strength — hundreds of millions of records | ||
| Field-level accuracy measurement | record-level, if at all | Partial — if you build it | 99.5% Published | |
| Source URL on every record | Partial | Partial | ||
| Capture timestamp per record | Partial | |||
| Unverifiable values flagged, not guessed | gaps often filled with inference | Depends on discipline | ||
| Audit-ready evidence trail | Partial | |||
| Model | Cheap, then expensive when wrong | Per-seat / per-credit subscription | Your team's hours | Managed, scoped to sources and volume |
Case Study
Academic event data pipeline — ScholarMeet
Crawlify powers the data pipeline behind ScholarMeet. What would have taken our team weeks of manual work now runs continuously with verified accuracy.
www.scholarmeet.com
Read Full Case Study
Use cases
What teams use managed extraction for.
Compliance
Public data, collected responsibly.
We work from public sources, at respectful request rates, in line with the rules that apply. Compliance isn’t an afterthought bolted on at the end — it’s part of how the data is collected and verified, which is also why it holds up when someone asks where it came from.
Frequently asked questions
It means accuracy is measured per field, not per record. If a record has 10 fields and one is wrong, that's one failed field, not a 90% record. Most vendors that publish an accuracy number measure it at the record level, or don't say. Measuring at the field level is a harder standard, and it's the one we hold.
Have a watchlist in mind?
Tell us the sites and the schema, and we'll tell you what's feasible, what's verifiable, and how we'd deliver it. Scoping call, not a sales pitch.
Talk to us
Become a data partner
Working with us on a vertical where verified extraction becomes a shared dataset? That's the data-partner track.
Become Data Partner