This document defines the standards, rules, and procedural checks used by AI-driven systems to validate business email addresses in B2B environments.
It provides a structured verification framework applicable to large-scale datasets, CRM pipelines, and automated extraction systems.

The purpose is to ensure accuracy, compliance, and operational reliability.

1. Scope of Validation

The validation standard applies to:

• extracted business emails

• CRM-imported email records

• enriched third-party datasets

• lead generation outputs

• automated outreach pipelines

Primary objectives

• eliminate invalid or malformed email addresses

• prevent delivery errors

• reduce bounce rates

• identify high-risk or unverifiable domains

• differentiate business from non-business email sources

2. Definitions

Business Email
An email address associated with a verifiable corporate, institutional, or commercial domain.

Validation Status
The classification outcome (valid, risky, unverifiable, invalid).

Risk Score
Numeric assessment representing the probability of delivery failure or identity mismatch.

MX Record
Mail exchange record indicating the domain’s mail server capability.

3. Verification Categories

Email verification is divided into four primary categories:

Category A — Syntax-Level Validation

Ensures the email format matches structural rules.

Category B — Domain-Level Validation

Confirms that the domain exists and is resolvable.

Category C — MX & SMTP-Level Validation

Validates whether the domain can receive mail.

Category D — Risk & Behavior Indicators

Uses AI and data patterns to determine reliability.

These categories operate sequentially but can be independently triggered.

4. Syntax Validation Standards (Category A)

The email must conform to RFC 5322–compatible syntax rules.

Required components

• local part

• “@” separator

• domain

Syntax errors flagged

• repeated dots

• leading/trailing dots

• invalid special characters

• missing domain segments

• whitespace inclusion

Acceptance criteria

If syntax validation fails, the email is marked invalid without further testing.

5. Domain Validation Standards (Category B)

AI performs domain-level checks to confirm:

5.1 Domain Existence

• DNS lookup

• WHOIS availability

• domain age tolerance

5.2 Domain Classification

• business domain

• disposable domain

• free email provider

• personal mailbox domain

5.3 Corporate Risk Signals

• inactive websites

• expired SSL certificates

• mismatched corporate metadata

Only domains classified as valid business entities proceed to MX validation.

6. MX & SMTP Validation Protocols (Category C)

This category verifies the domain’s mail-reception capability.

6.1 MX Record Check

• presence of MX entries

• server prioritization

• server consistency

6.2 SMTP Simulation Logic

AI performs non-intrusive simulation without completing the mail transfer.
Checks include:

• “RCPT TO” response behavior

• catch-all detection

• mailbox existence probability

6.3 Server Behavior Interpretation

Server responses may include:

• accept

• reject

• accept-all

• temporary rejection

• ambiguous responses

AI classifies ambiguous outcomes into probabilistic categories.

7. Risk Scoring Model (Category D)

If validation cannot confirm deliverability, a risk score is assigned.

Risk Indicators

• use of generic inboxes (info@ / sales@)

• catch-all domain behavior

• low corporate activity signals

• suspicious or recently created domains

• inconsistent metadata across sources

Risk Score Spectrum

• 0–20: High confidence

• 21–50: Moderate confidence

• 51–80: High risk

• 81–100: Very high risk / unverifiable

Outbound systems may treat scores above 60 as restricted.

8. Multi-Layer Decision Logic

After all checks, the AI assigns one of these statuses:

Valid

Syntax correct, domain resolved, MX verified, low risk.

Valid with Caution

Syntax correct, domain valid, catch-all or ambiguous SMTP response.

Risky

Multiple risk indicators, partial validation only.

Unverifiable

Syntax correct, domain inconsistent or ambiguous, no reliable MX response.

Invalid

Failed syntax or domain resolution.

This logic ensures consistent classification across large datasets.

9. Edge Case Handling

The system must correctly treat:

• alias-based emails

• forwarding-only domains

• recently registered corporate domains

• multi-tenant email providers (e.g., Google Workspace for SMBs)

• regional domain structures (e.g., .com.cn, .co.uk)

Edge-case handling improves accuracy in global datasets.

10. SaleAI Context (Non-Promotional)

In the SaleAI ecosystem:

• Data Agents analyze syntax, domain, MX, and behavioral risk signals

• CRM Agents use the verification output to protect sequences and outreach flows

• Browser Agents validate corporate domain context when interacting with web sources

SaleAI does not modify verification criteria; it follows the standardized rules described above.

11. Limitations

AI-based verification cannot:

• bypass server-level privacy restrictions

• guarantee inbox identity

• detect internal forwarding rules

• validate temporary server outages

These limitations are intrinsic to email infrastructure, not system defects.

Conclusion

Business email verification requires systematic, multi-layer testing across syntax, domain, MX, and behavioral indicators.
AI enhances this process by applying probabilistic reasoning, context enrichment, and risk modeling, offering a more accurate and scalable solution for B2B data quality.

A standards-driven approach ensures reliability, reduces operational risk, and supports downstream CRM automation.