haisol

An AI worker you message —
that checks its own work.

It runs one repetitive process in your business on its own. You talk to it like a person. And a separate program stops its bad output before anyone sees it.

Most teams that tried AI got a faster first draft and a slower second one. Someone still had to read everything, because roughly one output in ten was wrong and nobody knew which. The fix was never a better model. It was building the part that says no.

What you actually get

Four things, on day one.

01

Your own bot

On Telegram or Slack. You message it, assign work, ask what it did. It has a name and it answers.

02

The worker

Runs your process on a schedule without being asked. It does not wait for you to open a laptop.

03

The gate

A program that reads every output against your rules and refuses to pass the ones that break them.

04

A daily report

What it did, what it blocked, what it is stuck on. Measured from the work itself, not summarised by a model.

Your worker
online
how did today go?
Ran the check on 34 drafts.
29 passed. 5 blocked — 3 named a competitor, 2 promised a result.
The 29 are in the queue for your review.
why was #12 blocked?
It said "guaranteed results". Your rules ban outcome promises. I rewrote it and it passed on the second run.

The part nobody else builds

Software that says no.

Not a prompt asking the model to be careful — a separate program that compares output to your rules and exits with an error when it does not comply. Here is a real one, guarding a live storefront:

# copy the agent wanted to publish
$ python check_claims.py "clinically proven to cure back pain"

  [MEDICAL CLAIM]  'cure'
  [MEDICAL CLAIM]  'pain'
  [UNSUBSTANTIATED] 'clinically proven'

  TOTAL ISSUES: 8
  exit 1 — not published

The decision is not left to the model. The same pattern blocks an ad cut that breaks its brief, stops a price from drifting between two pages, and refuses to close a run while something is broken.

Where it earns its keep

Anywhere a person re-reads machine output.

Client copy

Checked against an approved facts document before anything is scheduled.

Creative volume

Every cut measured against the brief, so weak ones never reach review.

Reporting

Numbers pulled from the source and verified, never restated from memory.

Research and outreach

Every lead opened and confirmed before it enters the pipeline. No invented companies.

How it goes

Small, and provable.

You name one step

The place where checking machine output eats real hours.

I write back honestly

Whether a worker plus a gate would fix it. Free, and sometimes the answer is no.

It runs

The worker, the gate, the bot and the report — live on your rules.

Monthly after that

Maintenance, tuning as your rules change, one new workflow a month.

Tell me the step.

Describe the one process where checking AI output costs your team hours. I will send back a written assessment of whether this would actually fix it — no call required, and no charge either way.

ohad@haisol.net

Written reply, usually same day.

Describe the step

If it would not help, I will tell you that instead.