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Zencount AI

Ask your numbers anything.

An analyst that lives inside your model — it answers from your live plan, actuals and line items, shows you exactly what it read, and never writes a thing without your Confirm. Try it below.

Zencount AI · Acme Groupyour live data
ZMorning 👋 I read your plan and actuals — ask me anything, or tap a question below.
Try asking
Your monthly review now runs itself

Reviews on a schedule, findings in your inbox.

Tell it once — “check actuals vs. budget every 1st at 08:00, flag anything over plan” — and the routine runs daily, weekly or monthly. You’re notified only when something is noteworthy, and every run keeps a full transcript.

Routine · Monthly variance review
Monthly · 1st · 08:00 · Europe/Berlin
!Paid Acquisition6711 · ran hot in May–Jun+€19K
!Engineering · Salaries6111 · backend hire landed a month early+€8K
Hosting & Infrastructure6851 · optimization landed early−€11K
iRunway extendedLower burn pushes the zero-date out+0.6mo
Checking actuals vs. Budget 2026…
What it does

Four jobs, off your plate.

Not a chatbot bolted onto a dashboard. Every answer is built from tool calls against your live data — it never invents figures, and the tool chips show you what it read.

Answers with receipts

It aggregates the real entries, drills the actual line items, and cites versions and periods. “Explain” on a grid cell hands it your exact context.

Scenarios you confirm

Describe the downside in a sentence. The draft arrives as a previewed proposal — nothing is written until you click Confirm, and confirmed entries are tagged source=ai.

Routines on a schedule

Daily, weekly or monthly reviews with “Run now” — created straight from the chat. Notifications only when noteworthy, in the bell and by email.

Built for the big questions

Investor prep, a full plan review, savings potentials — broad tasks fan out into parallel deep-dive sub-analysts whose reports are synthesized into one briefing.

Get a feel for it

“What if we hire faster and spend more?”

Drag the assumptions and watch the outcome react. In the product you don’t drag sliders — you describe the change in chat, Zencount AI drafts the scenario version, and you confirm it into your model.

One sentence in chat becomes a previewed scenario proposal.
Confirmed scenarios land as a new version — ready in Compare.
Revenue EOY
2.13M
-7K vs base
Runway
15.3mo
-3.1mo vs base
Net burn / mo
222K
+38K vs base
The AI only sees what you see

Scoped by architecture, not by promise.

Every tool call runs under your database identity — the same row-level security and entity/department scoping as your login. There is no separate “AI access level” to audit, and your conversations stay private to you.

RLS
Tools execute under your identity — org isolation and dimension scoping apply automatically
0
writes without a human — proposals need your Confirm, routines are read-only
🔒
Conversations are private to you — not even org admins can read your chats
audit
Every run is measurable — tokens, tools and duration per run, transcripts included

Let an analyst
work your night shift.

Ask your first question against your own chart of accounts — answers with receipts, not hunches.

Get started →
It proposes. You decide.