The agent supervision company
Your customers see your AI agents as you. Pretxt keeps everything they say and do in line with your policies and your brand, so you can trust them with more.
Why supervision matters
United States · 2026
83%
of US consumers agree that the brand should be held accountable if an AI‑powered interaction goes wrong.
2026 Delight AI Index, survey of 1,000 US adults who used customer service, March 2026
Canada · 2024
Air Canada’s website chatbot told a grieving customer that a bereavement discount could be claimed after booking. The airline argued its chatbot was a separate legal entity, responsible for its own words. The tribunal disagreed and held the airline to its chatbot’s answer.
Germany · 2026
A clinic’s chatbot told people its doctors held specialist titles they didn’t have. The Higher Regional Court of Hamm held the clinic responsible for what its chatbot said, and found that a general warning about AI errors didn’t change that.
Higher Regional Court of Hamm, 12 May 2026, 4 UKl 3/25 (not yet final)
What supervision is
Supervision holds your AI agents to your standards while the work is happening, and guides them before a misstep reaches your customer or another system. Those standards cover more than security: accuracy, fairness, your brand, privacy and compliance.
Access, exfiltration, prompt injection.
Someone talks an agent into doing something it shouldn't: leaking a record, calling the wrong system, following an instruction buried in a document it was asked to read. The attack surface is every message it takes in.
Hallucination, and slow drift.
Wrong is easy to spot. Slightly wrong, consistently, for months is the expensive one: the figure that drifts, the policy paraphrased a little looser each week, the confident answer nobody thought to check.
Harm, toxicity, self-harm, crisis.
Someone in trouble asks a question the model was never built to hold. What counts as a safe answer isn't universal. A crisis line and a trading desk need opposite things from the same sentence.
Who it serves worse, and why.
The same agent performing differently depending on who is talking to it. Rarely a slur. More often a slower answer, a stricter reading, a decision that quietly goes the other way for one group of customers.
What your agent says about you, in public.
A thousand conversations a day, each one speaking as the company. Tone, claims, promises, what gets apologized for: all of it is brand, and none of it was in the style guide.
Knowing when not to answer.
The hardest judgment isn't the answer, it's knowing you shouldn't be the one giving it. Handing over late, or with nothing attached, costs more than never having tried.
PII, residency, retention, consent.
Personal data doesn't arrive labeled. It turns up mid-sentence, in an attachment, in a screenshot. The rules about where it may live and how long it may stay follow the customer, not the system holding it.
Who told it what, and what it did next.
Six months later somebody asks why. Not what the agent said, but what it was told, what it reached for, and what it decided in between. Either that record exists or the question has no answer.
The reason, in terms a human can check.
A log says what happened. It doesn't say why. Turn down a loan, flag a claim, refuse a request, and somebody is entitled to a reason they can argue with, not a trace they can only read.
SOC 2, ISO 42001, EU AI Act.
The rules were written for people: SOC 2, ISO 42001, the EU AI Act. They still apply when the decision is made in two hundred milliseconds by something that cannot be deposed.
Hover to skim · click for the full note
Informed by NIST AI RMF · MIT AI Risk Repository · OWASP Agentic Top 10
How supervision works
Two more steps keep making it better: test a plan against your own examples, and let Pretxt uncover the gaps you never thought of.
01 · Onboard
Your agent already has its job, and it keeps it. Connect it to Pretxt, and you’re ready to set what it’s held to.
For example: a support agent that already answers refund and delivery questions.
Explore onboard02 · Define
Write down your policies, your limits, and the promises your agent can make, in plain language. Pretxt turns each one into a rule, and the rules into a plan you can read. From that moment, supervision is running.
If a rule needs specialized judgment that doesn’t exist on Pretxt yet, the platform builds that capability itself and runs it through strict quality control, before we give it our own stamp of approval. It never becomes a ticket lost in a backlog.
For example: “You may issue refunds up to $100. Anything above that needs separate approval.”
Explore define03 · Test
Run a plan against situations from your own work: everyday requests, tricky exceptions, and attempts to push past your limits. You see what supervision would do in each one.
For example: a customer says “ignore the limit.” The limit stays.
Explore test04 · Uncover
Pretxt learns from your agents’ real work and surfaces what your plan doesn’t cover yet: the questions customers keep asking and the exceptions that keep coming up. Your team decides what to add, and the plan grows.
For example: delivery questions often hide a deadline that matters.
Explore uncoverAlways on Supervising, continuously, from the moment your first plan exists.
Every line of work, and every business in it, has its own standard for getting it right. Whether that’s a delivery promise, a marketing claim, a credit decision or a patient’s privacy. Explore a few use cases below.
Customer support
Let agents take on more of the everyday questions while your people focus on the customers who need them.
Explore the use caseMarketing
Give content agents room to create, with supervision that asks for evidence before a number goes out.
Explore the use caseFinancial Services
Help customers find their next step, with answers that stay tied to what the lender documented.
Explore the use caseHealthcare
Give healthcare agents guidance to support patients and recognize the moments that need the care team’s judgment.
Explore the use caseNo. Supervision is automatic in every interaction, and nothing waits on a person. Your team’s part is setting the standards and approving changes to them, not reviewing the work.
Yes. When supervising your work needs specialized judgment that doesn’t exist on Pretxt yet, the platform builds that capability itself and runs it through strict quality control, before we give it our own stamp of approval. It never becomes a ticket lost in a backlog.
Tell us what you want your agents to achieve. We’ll explore the use case, your priorities, and the right next step during an early-access conversation.
Bring us the work you have in mind, and we’ll work out where supervision fits.