AI pre-scan. Human review.
Errors found before your clients.

Our AI pre-scan reduces review costs by catching structural issues first. Then trained human reviewers find the errors that matter. No onboarding marathon. No complex integrations.

01

Submit your AI output

Send us anything your AI generated that needs to be verified before it goes to a client. Content, reports, data, communications. Submit via email, Slack, dashboard, or API.

What to include

The AI output, plus any source material you want us to verify against. If there's no source, we flag unverifiable claims. That's the point.

Formats we accept

Docs, PDFs, spreadsheets, plain text, HTML, raw data exports. If your AI can generate it, we can review it.

02

Our AI pre-scans for obvious faults

Before a human touches your submission, our proprietary intake system scans for obvious failures: broken formatting, clearly fabricated data, missing sections, structural problems. If something is fundamentally broken, we catch it here so your verifier doesn't waste time on work that needs to go back to your AI first.

What it catches

Structural defects, formatting failures, missing critical fields, obvious data corruption, and outputs that are clearly incomplete. The things that would make human review a waste of effort.

What it doesn't do

It does not verify accuracy, judge quality, or make pass/fail decisions. That's the human's job. The pre-scan exists to protect verifier time and your money.

03

A trained human verifier reviews it

A real person, specifically trained to catch the ways AI fails: hallucinations, confident fabrication, numerical drift, outdated references, tone mismatches, and logical gaps. The pre-scan already cleared the obvious failures, so your verifier focuses entirely on accuracy, quality, and nuance.

What they check

Every factual claim, every number, every name, every date, every source reference. They check logical flow, internal consistency, and whether conclusions follow from the evidence.

How they're trained

Our verifiers go through a structured training program covering AI failure modes, source verification methodology, and output-type-specific checklists. They're assessed continuously.

04

Get a clear error report back

You receive a report identifying what needs correction: errors, inconsistencies, and flagged issues. Critical problems are highlighted. You decide what to fix and what ships.

Report format

Line-level annotations identifying errors and flagged issues. Summary of critical problems at the top. Delivered in your preferred format.

Turnaround

Standard workloads are handled within normal operations. Higher-volume or specialized contracts include lead time and scheduling discussed during scoping.

Fits where you already work.

Email

Forward AI outputs to your dedicated HitLint inbox. Get verified results back in the same thread.

Slack

Submit and receive in a dedicated Slack channel. Real-time status updates on your reviews.

Dashboard

Upload, track, and review all verifications in one place. Full history, analytics, and team access.

API

Build verification directly into your production pipeline. Submit programmatically, receive structured results.

Who's checking your work?

Fair question. Our verifiers aren't random freelancers pulled from a marketplace. They're trained professionals working in structured teams with continuous quality oversight.

40+hrs

Initial training on AI failure modes and verification methodology before touching a live review

Weekly

Calibration sessions where verifiers review the same output independently and align standards

100%

Of new verifier work is double-checked by senior reviewers during their first 30 days

Live

Performance scoring across accuracy, speed, and consistency. Below threshold triggers retraining.

Questions we get asked.

We use AI at the intake stage to pre-scan submissions and catch obvious faults before a human touches them. This is an efficiency layer that prevents wasted effort. But the actual verification, the accuracy checks, the hallucination detection, the quality judgment, is 100% human. AI finds the obvious problems. Humans find the subtle ones. That's the division.

All verifiers sign NDAs. We offer dedicated teams for sensitive work. Client content is not retained after review completion and is never shared with other clients. What we do keep: anonymized verification patterns, meaning the types of errors caught and the methods that caught them. This is how we continuously improve our verification methodology. We learn from how AI fails, not from your data.

For Pipeline and Embedded tiers, we build custom verification checklists based on your output types, brand guidelines, and quality standards. Your dedicated team learns your specific requirements.

You get a clear report identifying errors and flagged issues. We tell you what we found. You decide what to correct and what to ship. The goal is to surface problems, not to certify accuracy.

Standard workloads are handled within normal operations. For significant volume increases or higher-value contracts, we discuss lead time during scoping to ensure we have the right team allocated. Our infrastructure is built to scale with you.

Ready to add a human checkpoint?

Takes 5 minutes to set up. Send us your first output today.

Scope Your Verification