LeadQC by Zeplinix, B2B lead quality checkby Zeplinix
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Live B2B lead quality check

From sourced data
to GTM-ready.

Every prospect re-checked against 60+ live signals, corrected, enriched and qualified by your rules, before it reaches a campaign.

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Your source is the starting point.
LeadQC makes the quality decision.

Wherever the file comes from, every record is re-checked, corrected, enriched and qualified, then resolved into three files.

Sources
  • Apollo
  • Lusha
  • ZoomInfo
  • GigaSheet
  • Blitz
  • Cognism
  • CRM
  • Vendor file
  • CSV / XLSX
  • API / cloud
Live intake · 10,000 records · one run
Live quality engine
ValidateCorrectEnrichQualify
In transitBatch 149Validating…
14,821/ 20,000
Checked live
Resolves into
01ErrorHeld back, with reasons
02Corrected + enrichedWhat changed and what was added
03GTM-readyDelivery-ready population

Representative upstream data sources. Logos and names do not imply partnership or native integration. Counts are illustrative.

Your source tells you what it knew.
LeadQC checks what is true now.

Every record · re-checked live at QC time
Traditional database enrichment
  • Stored data snapshot
  • Dependent on database freshness
  • Returns what the database already knew
  • May have changed since collection
LeadQC live quality
  • Re-check at the point of QC
  • Current employment and business signals
  • Live contact validation
  • Correct what changed · enrich what is missing
  • Apply your QC rules · explain the decision
Record transformationChecked live
Sourced recordLive checkCurrent record
EmployerBellcastle Inc. Employer A → B EmployerBellcastle Technologies
TitleVP Sales Old title → current title TitleChief Revenue Officer
Emailr.whitfield@… Email → revalidated EmailRevalidated · deliverable
Companynot in file Company information → refreshed Company742 employees · Boston, MA
TimelineCurrent (listed) Employment timeline → updated TimelineMoved Feb 2026 · 7 mo

Illustrative record.

"Enrichment is only as valuable as the data underneath it."

Live validation, correction and enrichment, at the point of QC.

One prospect. 60+ quality signals.
Checked together. Live.

Four signal streams, one current picture, including employment timelines with dates and durations, current and previous.

60+ signals · every record
Identity10 signals
  • First name
  • Last name
  • Full-name consistency
  • Identity verification
  • Professional profile match
  • Duplicate detection
  • Record freshness
  • Identity conflicts
  • Profile availability
  • Contact consistency
Employment19 signals
  • Current employer
  • Previous employer
  • Current title
  • Previous title
  • Department
  • Function
  • Seniority
  • Employment status
  • Current company start date
  • Current tenure
  • Previous company start date
  • Previous company end date
  • Previous tenure
  • Job change
  • Employer mismatch
  • Role change
  • Employment history
  • Current professional status
  • Employment consistency
Company19 signals
  • Company name
  • Legal / trading name
  • Domain
  • Domain health
  • Industry
  • Sub-industry
  • Employee size
  • Company status
  • Revenue / firmographics
  • Company address
  • HQ address
  • Branch locations
  • City
  • State
  • Country
  • Geography
  • Parent company
  • Subsidiary relationship
  • Location consistency
Contact11 signals
  • Primary email
  • Additional emails
  • Email validity
  • Email deliverability
  • Mailbox status
  • Business phone
  • Additional phone information
  • Address information
  • Contact consistency
  • Professional profile
  • Contact freshness
Example prospect · live R. Whitfield Chief Revenue Officer · Bellcastle Technologies
Employment timeline
Bellcastle TechnologiesCRO · Feb 2026 – now · 7 mo
Bellcastle Inc.VP Sales · 2019 – 2026 · 5 yrs 6 mo
Northwind SystemsSales Director · 2016 – 2019 · 3 yrs 4 mo
0signals checked

Signals are checked at the moment of QC. Availability depends on the record and the data available at that time. Illustrative prospect.

LeadQC doesn't just find invalid fields.
It understands when a contact may be dead.

LeadQC detects the condition. Your QC policy decides what it means.

No longer at listed companyEmployer mismatchJob changedRole changedOpen to workRetiredFreelancer / independentDual employmentConflicting active employmentStale professional profileMailbox unavailableInvalid emailChanged company domainInactive companyDuplicate / recycled contactOutdated contact informationCampaign-specific mismatchLong tenure conditionSame title for a company-defined durationOther company-specific rules
SignalSame title, 10+ years
+
Your QC ruleCompany A: long tenure → review
Company B: acceptable
=
VerdictReviewPassSame signal, two valid outcomes. Long tenure does not automatically mean a bad lead.
Contextual matchingQuality control should understand intent, not just exact strings.
Campaign ruleFinanceRecordFinancial ControllerContextual match
Required seniorityVP+ActualVice President, FinanceQualified

There is no universal definition
of clean B2B data.

LeadQC provides the quality intelligence. You decide what passes.

Your policy · applied to every record
  1. Layer 01LeadQC base quality60+ underlying signals
  2. Layer 02Your company QC policyYour definition of clean, dead, invalid, review and reject
  3. Layer 03Client / campaign rulesICP · RFP · TAL · Industry · Employee size · Geography · Function · Seniority · Exclusions · Contact limits · Custom conditions
  4. Layer 04Final quality decisionPass · Review · Reject, each with the reason
Your QC policy · interactiveTry the switches
Record under evaluation R. Whitfield · Chief Revenue Officer Bellcastle Technologies · 742 employees · verified business email · in role 7 months, moved Feb 2026 · previous title held 5 yrs 6 mo
  • Seniority: Director and aboveRecord: Chief Revenue Officer
  • Employee size: 200 to 5,000Record: 742 employees
  • Require a verified business emailRecord: Verified at QC
  • Review if job changed in the last 12 monthsRecord: Moved 7 months ago
  • Exclude companies under 1,000 staffRecord: 742 employees
Final quality decisionPassMeets all 3 enabled rules

Shown on one record so you can follow the logic. In a run, LeadQC applies your whole policy to every record in a fraction of a second.

One run. Three clear outputs.

Nothing disappears inside a black box. Every decision carries its reason.

One runcampaign_sep.csv10,000 records in, three files out
01Error

Records held back, each with the rule it failed and the signal behind it.

Record · Reason · Failed rule · Signal
02Corrected + enriched

Every record with what LeadQC changed, what it added, and where the current value came from.

Sourced value · Current value · Added attributes
03GTM-ready

The qualified population after your QC rules. Current, validated and ready for delivery.

Qualified · Current · Validated

The three files are views of one run and can overlap.

What changes when
QC becomes infrastructure?

One anonymised B2B demand-generation operation, before and after.

Before
  • Manual QC
  • Second QC layer
  • Large operational dependency
  • Inconsistent interpretation
  • Slow turnaround
LeadQC implemented
  • Live validation
  • Automated correction
  • Live enrichment
  • Company QC rules encoded
  • Explainable outputs
After
  • QC workflow optimised
  • Near 100% accuracy*
  • Second manual QC layer removed
  • QC operation now runs through LeadQC
  • Significant reduction in manual QC dependency
30M+records quality-checked & enriched last month
60+quality signals per prospect
~1,000records processed every 3 minutes
55–60%QC operations cost reduction

* Observed on this operation's configured rules. Figures are company-reported and vary by dataset, QC configuration and operating baseline. This is one operating case. We'd love to walk you through the workflow, the rules and what changed on a call.

Security & trust
  • Encryption in transit
  • Encryption at rest
  • Workspace isolation
  • DPA available
  • Retention controls
  • No training on customer files
  • Auditability
  • Explainable QC decisions

How we handle your data → Published privacy policy, terms and GDPR statement. Production files move through the authenticated product flow, not this page.

Names withheld.
Numbers kept.

Two operations that moved their quality check onto LeadQC. Anonymised here; names shared on request.

Case file 01
65%lower QC headcount cost
Near 100%accuracy on their rules
5Mrecords a month
Demand generation Client

Two manual QC layers, replaced by one live engine.

Largest B2B demand-gen operation on LeadQC

Before
  • Two manual QC layers, each with its own interpretation
  • Slow turnaround between sourcing and campaign
  • Fields taken at face value from the source file
With LeadQC
  • Automated correction and live enrichment at the point of QC
  • Company QC policy encoded once, applied to every record
  • Extra signals surfaced more sellable records, lifting revenue from the same data
Case file 02
80%lower sourcing cost
300Mrecords re-checked
Everysource, one policy
Multi-source data team Client

A 300M-record shelf, mostly dead contacts, turned back into pipeline.

Many platforms, one 300M-record shelf

Before
  • Data from many platforms, no consistent quality check
  • Most of the shelf was dead contacts nobody could trust
  • Fresh data bought again and again to replace it
With LeadQC
  • Shelf re-checked live: usable records revived, dead ones flagged with reasons
  • One QC policy across every source and vendor file
  • Sourcing spend down near 80%, with more usable records out

Client names withheld here under agreement and shared on request: ask for a reference. Figures are client-reported on their configured QC rules and vary by dataset, QC configuration and operating baseline.

Questions

Lead quality check, answered.

What a live B2B lead quality check covers, what data enrichment adds, and how LeadQC by Zeplinix fits your lead gen workflow.

What is a B2B lead quality check?

A B2B lead quality check re-checks every sourced record against current signals: does the person still work there, is the domain live, is the email deliverable, does seniority match your ICP. LeadQC runs that check live against 60+ signals, corrects what changed and flags what cannot be trusted, before the list reaches a campaign.

What does LeadQC's data enrichment add?

Where a field is missing or stale, LeadQC fills it from current sources: verified domain, seniority, employee size, employment timeline with dates and durations, location consistency. Enrichment runs in the same pass as validation, so the corrected record and the reason for each change arrive together in the enriched file.

How is this different from a lead gen quality check done by a vendor or by hand?

Vendor QA checks a file once, at delivery. Manual spot checks cover a sample. LeadQC re-checks every record live against your own QC rules, logs the reason for every decision and returns three files: errors with reasons, corrected and enriched records, and a GTM-ready list.

Which sources can I run through LeadQC?

Any B2B list: exports from Apollo, ZoomInfo, Lusha, Cognism, Blitz or Gigasheet, vendor deliveries, CRM exports, CSV or XLSX files, or records sent through the API. Named providers are examples of sources our customers use. LeadQC is independent and not affiliated with them.

How fast is a run?

A 10,000-record file typically comes back in about 14 minutes with all three outputs. The upfront file processing takes most of that time; the live checks themselves are fast.

Who builds LeadQC?

LeadQC is built and operated by Zeplinix Technologies Private Limited, a B2B operation automation company. Zeplinix's Lead QC is used by demand generation and revenue operations teams that source data at volume and need it campaign-ready. Reach the team at hello@zeplinix.com.

Is my data safe?

Files are processed for your workspace only, never used to train models or pooled with other customers, and deleted after 90 days or sooner on request. Our controls are SOC 2-aligned and we do not claim certification. The Security page lists every control.

Don't take our word for it.

Run your file.

Book a 20-minute walkthrough on a time that suits you, or request free test credits with the form. Upload a real file, apply your actual QC rules, and compare the output yourself.

No sample dataset. No polished benchmark.
Your data. Your rules. Your output.

Book a 20-minute walkthrough