PSA is the check before send — every AI-assisted message verified accurate, on-brand, and defensible before it leaves the building.
Before it ships. Not after it breaks.Plumbline and Stride are live today · Warden in early access
99% of executives say guardrails on AI-generated content would be valuable. Only 33% rate their own as strong and consistently applied.
Markup AI, “The AI Trust Gap,” 2025 ↗Nearly 40% of the time AI saves is lost to rework — correcting, rewriting, and verifying its output.
Workday, Jan 2026 ↗Fewer than 1 in 10 companies have a comprehensive framework for governing AI content.
SAS / Coleman Parkes, 2024 ↗Every figure on this page links to its primary source.
The AI-safety industry points inward — at the model, the API, the policy dashboard. None of it touches the AI slop that goes out the door under your name: the off-brand, inaccurate, almost-right content that erodes trust and burns hours in re-checking.
The message is where your company meets the world. That is the layer PSA owns.
One pass before anything ships — a customer email, a press statement, a board memo, a campaign. The model drafts. PSA decides whether it is safe to send.
Hallucinated statistics, fabricated sources, off-policy claims, and missing disclosures — surfaced before a human ever hits send.
Against your standard, not generic rules: your brand voice, your approved language, your claims register — defined once, enforced for everyone.
Fixes applied, sign-off logged. What ships is accurate, on-brand, and defensible — with a tamper-evident record that it was checked.
Not projections — documented cases, each linked to the primary record.
Deloitte Australia refunded part of a A$440,000 government contract after its report cited academic sources that did not exist — AI-fabricated citations in finished, delivered work.
Read the record ↗Air Canada was held liable after its website chatbot invented a refund process that did not exist. The tribunal rejected the airline’s argument that the chatbot was responsible for itself.
Moffatt v. Air Canada, 2024 BCCRT 149 ↗A syndicated summer reading list ran in print with 10 of 15 books that did not exist — invented by AI, attributed to real authors, and cleared by every human step except the one that checks.
The paper’s own account ↗Different industries, the same failure: confident AI output, no check at the moment of send. Each happened at an organization with reviewers, editors, or counsel on staff.
Three governed surfaces — the message, the seller, the agent — with one improvement layer underneath that makes the whole team measurably better.
The check before send. Catches the hallucinated statistic, the off-policy claim, and the missing disclosure before anything ships — and seals a defensible record of every send.
For the executive who signs off · marketing, comms, and the teams they answer to Live Govern seller AIGoverned AI for seller productivity. Reps draft at AI speed while your playbook, voice, and approved claims are enforced inline — speed without new risk.
For revenue leadership · CRO, sales ops, enablement Early access Govern agentsAs agents stop drafting and start acting, Warden checks every proposed action against policy at runtime — allowed, blocked, or escalated, all on the record.
For the CISO and risk owners · 76% of organizations are deploying or planning agentic AI within a year; 56% are familiar with the risks (EY, 2025 ↗)Ships inside every product. Loop watches where AI actually falls short in your team’s real work, turns each recurring gap into a targeted training, and measures whether the gap closes. A completion record proves attendance; a closing gap curve proves competence.
The same platform, read four ways. Every outcome carries the metric a pilot would be measured on.
Every AI-assisted message is checked against your brand voice and approved language before it leaves the building.
A tamper-evident trail of what was checked, fixed, and cleared — ready for the board, counsel, or anyone who asks.
Each flag becomes targeted training, so the same off-brand error doesn’t keep happening.
Governed AI in the rep’s flow — outreach, follow-ups, proposals — without the brand or claims risk.
Less of the rep’s day lost re-checking AI output by hand — the calculator below puts a number on it.
New reps get coached on the exact gaps the workflow surfaces — not a generic course.
As agents start acting, every proposed action is checked against policy and blocked or escalated before impact.
The accuracy, IP, and claims risks in outbound AI content are caught pre-send, not post-incident.
Proof the team is getting measurably better with AI — tied to real workflow behavior, not an attendance log.
The workflow detects where AI actually falls short and builds the targeted training — included with every product.
Show the board the curve of recurring gaps declining over time, not a stack of certificates.
Teams learn to trust and challenge the AI, so the speed gain doesn’t come back as rework.
Roughly 40% of the time AI saves is lost to re-checking its output. Set the three inputs to your team and read the cost.
Directional estimate, not a quote. Bring it to the Gap Check and we’ll pressure-test it against your real numbers.
recoverable per year by automating the pre-send check
Assumes ~40% of AI-assisted time goes to correcting, rewriting, and verifying output (Workday, Jan 2026 ↗), of which the automated check reclaims a conservative ~60%.
Twenty minutes. We pressure-test how AI content actually ships in your organization and show you what’s slipping through — before it ships for you.
A principal reads every request. If there’s a fit, you’ll hear back within two business days.