Adopt AI in revenue without adopting the risk.
AI stays off until you switch it on, per workflow. It suggests, a person decides, and every suggestion is tied to the decision it describes. Your reviewer can read all of it first.
Gate it, scope it, log it. In SalesSynq every AI helper is off until someone with the authority switches that one on. Code works out the answer; AI only writes the explanation. A person approves anything that matters. And every suggestion lands in a record nobody can edit afterwards.
Why does the AI project stall at the security review?
Because you are asked for evidence and the vendor supplies adjectives. The questionnaire wants to know what the model decides, what data leaves the building, what happens when it is wrong, and what an auditor will be able to see in nine months. The answers come back as a slide about responsible AI, and your reviewer — correctly — declines to sign.
You should not have to find out in the QBR. You should not have to choose between moving the quarter and passing the review either. But that is the choice you are handed, and you know how it resolves: the project sits, the quarter passes, the deals keep slipping for the same reasons as last year, and the org goes on making its decisions exactly the way it always has. Meanwhile your reviewer is not being obstructive. Nobody can approve what they cannot inspect.
A revenue leader should not have to guess, and a reviewer should not have to take a vendor's word for it. Both are solvable with the same thing: let them read the controls before anyone books a call.
What is the AI actually allowed to do here?
Write sentences. That is the whole job. The useful consequence is that your governance conversation stops being about the model at all — you are not asking whether a language model can be trusted with your forecast, because it never had your forecast.
- 1
Nothing is on until you turn it on
Eleven places where AI can help, and every one of them is off until somebody with the authority switches that one on. Not a single global AI toggle, and nothing running on an opt-out basis while you decide.
- 2
The model does not make the decision
Code works out the score, the state and the scenario. The language model only writes the sentence that explains them. That separation is built into how the product runs, not written into a guideline someone could relax under deadline.
- 3
The explanation cannot drift from the answer
Each sentence is tied to the exact result it explains, and quotes come from your own data rather than from the model. If the two ever come apart, you do not see the sentence at all.
- 4
A person approves anything that matters
Propose, review, approve. The assistant cannot change a shared dashboard, does not write to your CRM records, and cannot show anyone data they are not already entitled to see. Sending a task out to a work tool is a separate permission you grant one tool at a time.
| Dimension | SalesSynq | Typical AI revenue tool |
|---|---|---|
| What is on when you sign | Nothing. Eleven AI helpers, each one off until somebody with the authority switches that one on. | On, with an admin opt-out — the governance conversation happens after the feature is already live. |
| Who decides | Code works out the answer; the model writes the explanation, tied to that exact answer. | The model produces the answer and the explanation, so the two cannot be checked against each other. |
| What a reviewer gets up front | A public record of what the AI does and the rules it runs under — readable before any call or NDA. | A sales deck and a trust page, on request, under NDA. |
| Mood and personality | Refused by the product. There is nowhere for it to be stored. | Addressed in an acceptable-use policy, enforced by convention. |
| Evidence nine months later | A record of every suggestion that nobody can edit, plus the evidence behind each published score. | Application logs, retained per the standard retention schedule. |
This table compares architecture and approach. Descriptions of other tools reflect their published design and are not performance or superiority comparisons.
How do I get there?
SalesSynq spots at-risk deals early and tells your team exactly what to do next. Three steps, and your reviewer can start reading before step one.
- 1
Connect your CRM
HubSpot connects read-only in a few minutes, and nothing in your CRM changes. Every AI helper is still off at this point — the product is useful before a single one is switched on.
- 2
See what is actually at risk
Your pipeline comes back scored against the evidence behind each deal. Your reviewer can already open a score and see exactly what it was based on, which is usually the question that stalled the last vendor.
- 3
Act while it still matters
Switch on only the AI helpers you want, one at a time, with a person approving anything that matters. Revoke any of them later and it goes quiet again the same day.
What can my reviewer check before the first call?
Everything they need in order to decide whether the call is worth taking. What the AI does, what it is not allowed to do, and how each of those is held in place — published openly, so a CISO or a DPO can read it directly instead of asking us for it and waiting.
No account. No NDA. No sales conversation. Send your reviewer this before you send them a calendar invite:
What our AI does, and the rules it runs under →It lists every place AI is used in the product, which version of the rules is in force, and the controls each use is held to. If their tooling would rather read it than click through, the same record comes as a file at /ai-disclosure.
That record is our own description of how the product is built and governed, published with the controls that back it. It is not a legal opinion and not a claim of regulatory status.
What can nobody switch off?
The floors. These are what make the product safe to buy for a regulated employer, and they are deliberately not configurable — a control an administrator can lower is a control your works council should assume is already lowered.
Nobody gets a personal score
SalesSynq scores deals and teams, never individual people. There is no plan, tier or contract that turns it into a way to rank your reps, and no setting that reveals one.
Aggregate reporting starts at five by default
Aggregate reporting suppresses groups below five by default. A workspace administrator may raise that threshold or lower it no further than two. Individual scorecards, rankings and performance metrics remain prohibited.
Mood and personality are refused outright
Model-derived emotion, sentiment, tone and personality fields from workplace messages are discarded, rejected at the storage boundary and never used in scores or recommended actions.
Hard bans stay hard; publication policy stays visible
Named-person scoring and workplace-inference storage cannot be enabled. Publication settings are explicit instead: the trusted-signal gate defaults to three, with documented legacy one-signal or disabled policies, and group suppression defaults to five with a hard configurable minimum of two.
SalesSynq publishes scores for deals and aggregate teams, never performance scores or rankings for named people. That is enforced in the product, not promised in a policy.
What does my auditor get afterwards?
A record written for somebody who was not in the room. Governance that only exists while the vendor is on the call is not governance, so everything below is readable months later by a person who has never met us.
- Every AI suggestion is written to a customer record that cannot be edited or deleted.
- Every published score shows exactly what it looked at, which risks it weighed, and what it could not see.
- There is a screen listing what SalesSynq would not score and why — something your reviewer can open, not something buried in a file.
- Alerts that could not be delivered are recorded rather than quietly dropped, and anything that does not clear the interruption bar rolls into a digest.
- Turning a helper off is recorded the same way turning it on was, so the history of who allowed what is complete.
When the evidence is too thin, SalesSynq tells you it does not know instead of guessing — and shows you what it could not see. In the same spirit, here is what we will not claim — worth weighing just as heavily as the list above:
- We publish no SalesSynq performance score. Generated certification fixtures test deterministic machinery; they are not predictive evidence.
- Your data is never pooled with another company's, and we never rank you against anybody else.
- We describe where we think the product lands under the EU AI Act and show the controls that back it. We do not claim a certification we do not hold.
Get this right and the argument ends. Your reviewer signs, because they read the controls before they met you. Your CRO gets the tool this quarter rather than next year. And when somebody asks nine months from now what the AI did on that deal, there is a record that answers — and nobody has to go looking for the person who was there.
Questions from the governance side of the table
Let your CRO and your reviewer read the same page
Start with the record your reviewer can read without talking to us. Then bring your own pipeline and see what is at risk — with every AI helper still switched off.
Private beta is invite-only and requires approval. General availability targeted for Q3 2026.
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