Nobody at HKR checks the bank for new payments. Every hour from 7:00 to 20:00, the AI checks Wise and Banca Transilvania and tells the team who paid. A person still marks each payment paid.

Every hour from 7:00 to 20:00, the AI checks Wise for new incoming transfers. Banca Transilvania sends a text when money lands, and the AI reads those texts in the same pass. Each payment is checked against the open invoices.

The result goes to the team’s Slack channel: who paid, how much, and which invoices it clears. On Wise, a transfer between two HKR companies is named as an internal transfer and matched to no invoice. A person still marks each payment paid in Zoho Books.

Nobody at HKR works out by hand which invoices a payment clears. The AI clears the oldest invoice first and asks a person about any amount that does not fit. A person marks each payment paid.

A payer’s name rarely matches the name on the invoice, and a partial payment rarely matches an invoice total. The AI keeps a copy of the open invoices, refreshed four times a day, and finds the client who sent each payment. When the payment could clear several invoices, the oldest goes first.

When the amount does not fit an invoice total, the AI shows how it would split the payment and asks a person to confirm. When it cannot tell who paid, it says so and leaves the payment for a person to place. A person marks each payment paid in Zoho Books.

Nobody at HKR collects balances bank by bank. The AI refreshes Wise and Revolut each working hour, reads Banca Transilvania’s statement when it arrives each day, and shows the age of every balance. A person names the owner of any account it does not know.

HKR banks with Wise, Revolut and Banca Transilvania, across three companies and four currencies. Wise and Revolut balances refresh every working hour. Banca Transilvania sends one statement a day, and the AI reads it when it arrives. A few accounts are typed in by hand. Every balance shows how old it is, so nobody reads yesterday’s number as today’s.

Each account belongs to one HKR company. When the AI finds an account it does not know, it holds that account until a person names its owner. The question “how much do we have” gets one answer.

Nobody at HKR copies numbers out of the books for a report. Four times a day, the AI copies invoices, expenses, customers and payments from Zoho Books, so every report reads the same numbers. People still keep the books and decide what goes in them.

HKR keeps its accounts in Zoho Books. Four times a day, the AI copies the new and changed invoices, expenses, customers and payments into one database. Reports read from that copy, so two people who ask the same question get the same number.

The copy only reads the books. Invoices, corrections and every other entry stay in Zoho Books, with the people who keep them.

Nobody at HKR builds the overdue list by hand. On the 5th and the 15th, the AI shows the whole team every overdue invoice and how late it is. People do the chasing.

Twice a month, on the 5th and the 15th, the AI posts every invoice past its due date in the team’s Slack channel, with how many days late each one is. Everyone sees the same list on the same day.

The AI only lists. People decide who to chase, when and how, and a person records each payment when it arrives.

Nobody at HKR reads every bill for surprises. On the 18th of each month, the AI checks each expense against what that vendor usually charges and lists what stands out, with the reason. A person decides what each one means.

A large bill tells you nothing until you know what that vendor usually charges. On the 18th of every month, the AI checks each expense in the books against the vendor’s own history: a single bill far above its usual size, a vendor that was not there in the last six months, a software tool that stopped charging.

The flags come back in Slack as one list, alerts first, then warnings, each with its reason. A person decides what each one means. The AI reads the books and never writes to them.

Nobody at HKR re-reads past months for bills that came in late. On the 18th, the AI fetches three months of expenses again, so late bills count, and ranks what moved, with the reason. A person decides what each change means.

A bill booked late changes a month that already looked finished. On the 18th of every month, the AI fetches the last three months of expenses again and scores them on nine checks: category swings, large single bills, capital spending that drifts, expenses without a category label and more.

The result lands in Slack: the total, the change month on month and year on year, and the lines that moved, each with its reason. A person decides what each change means. The AI reads the books and never writes to them.

Nobody on HKR’s finance team digs through folders and the books for an answer. They ask the AI in Slack, and it answers from the company’s records: contracts, payments, spend and payroll rules. The person who asked decides what to do with the answer.

The finance team asks in Slack, in plain words: what a contract says, whether a client has paid, what we spend on a vendor, what a payroll rule allows. The AI looks it up in the books, the signed contracts and the company’s other records, and replies in the same thread.

Contracts come up most often, then payments, follow-up tasks, spend and payroll rules. The AI finds and reports. The person who asked decides what the answer means.

Nobody at HKR ties salary and contractor payments to people by hand. Every week, the AI ties each payment to a person and lists the ones that do not tie. A person resolves each one on the list.

Every Monday, the AI goes through the salary and contractor payments in the books and ties each one to the person it paid, using the HR records.

A payment it cannot tie goes on a short list, and a person resolves each one. When every payment ties, no list is sent, so a list arrives only when there is work on it.

Nobody at HKR searches folders for a signed contract. Every signed document is in one index, so “what did we sign with this client” is a question the AI answers. A person decides what the contract means.

Every day, the AI walks the folders where HKR files its signed documents and adds each new one to a single index, with who signed it and what kind of document it is.

So “what did we sign with this client” is one question in Slack, with no folder search. The AI finds the documents and says where they are. A person reads them and decides what they mean.

Nobody at HKR rebuilds the forecast by hand. On request, the AI rebuilds it from the books and lays cost-cut scenarios over it on one chart. A person picks the plan.

The forecast is rebuilt only when someone asks for it, from the books as they stand that day.

Cost-cut scenarios sit over the forecast on one chart, so each option is compared on the same numbers. The AI lays out the options. A person picks the plan.

Most deal updates now come in from chat: the team says what happened, and the AI writes the note, the stage and the next task. A person says yes before anything is saved.

Say what happened on a deal in chat, the way you would tell a colleague. The AI finds the deal, writes the note, updates the stage and sets the next task, then asks before it saves anything.

When a task list fills up with leftovers from old meetings, the AI sorts them from the live work and clears the leftovers on one yes. Nothing in the CRM changes without a person’s yes.

Nobody at HKR has to go looking for stuck deals. Every weekday morning, the AI flags each open deal that went quiet, passed its close date or has no notes, and a person decides what happens to it.

Every weekday morning, the AI goes through each open deal. It flags a deal with no activity for 14 days, a deal past its close date and a deal with no notes, and suggests a next step for each one in the team’s chat.

The flag comes back every 7 days until someone acts; one deal in our own pipeline was flagged about ten times. The AI changes nothing in the CRM on its own, and a person decides what happens to each deal.

Nobody at HKR has to re-read a deal’s whole email thread before a buyer call. On request, the AI reads the emails and notes and returns a brief, the open questions and the terms to quote, and the rep runs the call.

Before a buyer call, the rep asks the AI to read the deal. It reads the email thread and the deal notes, then gives back a short brief, the questions still open and the contract terms to quote. The rep runs the call.

The rep can also ask whether a deal can convert. The AI reads the same emails and notes and says whether it can, and why, so the rep sees the reasoning and can overrule it.

Nobody at HKR has to hunt for prospects or watch clients’ careers pages. The AI brings new prospects each weekday and flags the roles our clients open that we could fill, and people decide whom to approach.

Each weekday, our sales lead gets new prospects: why each one fits, where the AI found it and the next step. A name comes back only when something about it has changed.

The AI also watches each client’s job boards and careers page. When a client opens a role we could fill, our account lead hears about it. People decide whom to approach.

Nobody at HKR has to build a prospect list by hand. Name a client you want more of, the AI returns similar companies in tiers, and the rep picks whom to contact.

Name a client you want more of. The AI finds similar companies, sorts them into tiers and names the person most likely to decide at each one.

For each email address, it says how sure it is. The rep picks whom to contact.

Nobody at HKR has to look a company up by hand before writing to it. Paste a name, the AI says what the company sells, to whom and how big it is, and the rep decides if it fits.

Paste a company name in chat, and the AI says what the company sells, to whom and how big it is.

For a Romanian company, it reads the accounts the company filed: revenue, headcount, profit and sector. The rep decides whether the company fits.

Nobody at HKR has to start a first email, a partner chase or the rep’s weekly report from a blank page. The AI drafts each one, and a person edits and sends every one.

The AI writes first messages to new prospects in the rep’s own voice, and on Friday it drafts the rep’s weekly report. Every Wednesday, it lists each partner ask that has waited two weeks, names who owes the next move and drafts the chase.

Emails wait as drafts. The AI never sends a message, and a person edits and sends every one.