An AI that does the work, not just answers about it
Tali runs any operation on the platform with the permissions of whoever asks, and confirms before writing. Ready-made agents take care of accounting and finance. Agents inside process steps read documents, classify and fill in. And the assistant you already use, such as ChatGPT, Claude or Gemini, reaches your data through TAI's MCP server, under the same rules.
People decide. Agents execute.
What a bolted-on AI cannot do
It answers, but does not act. The chat explains how to open payroll. Someone still has to open it, calculate, approve and pay, screen by screen.
It does not know who you are. An AI outside the system does not carry your permissions, so it either sees too much or nothing at all. Both are a problem.
It does not have the data. To answer about the operation, someone exports a spreadsheet. By the time the answer arrives, the number has changed.
It leaves no trail. What the AI suggested, who confirmed it and what was saved must sit on the same audit trail as everything else in the company.
Runs with your permissions and confirms before saving
Every TAI agent calls the same operations the screens call. It has no back door: the permission is the requester's, the business rule is the server's and the result lands on the same trail. That is what makes it safe to let the AI do things, not just suggest them.
Same permission as the screen
The agent sees and does exactly what the person can see and do. Nothing more, nothing hidden.
Confirmation before writing
Reads are immediate. Writes show what will be saved and wait for your yes; irreversible acts, such as approving or paying, ask for a second gesture with a preview.
Results as cards, not prose
A payroll, a ticket, a cash flow arrive as a card in the conversation, with a button to open the screen.
Audit trail
What the agent executed is recorded with who asked, when and what, like any action taken through the screen.
Four ways to have an agent working for your company
They rely on the same base, the same records and the same permissions. The difference is where each one comes in.
There is no single robot doing everything. There is Tali running the platform in conversation, specialised agents on routines with a beginning, middle and end, agents inside process steps, and your own assistant connected from outside.
Where each agent comes in
Tali, in conversation
Open it from any screen, ask in plain language and it executes: opens payroll, clocks in, creates the ticket, builds the process, generates the payslip as PDF.
Ready-made agents by area
The accounting agent closes the month for the firm's whole client base. The finance agent reconciles the statement and projects cash. Each one gets ahead where it can and shows where a decision of yours is missing.
Agents inside process steps
Inside a flow, a step can have an agent that reads the attachment, classifies, fills in the field or drafts the document before the person decides.
Your own agent
ChatGPT, Claude, Gemini or your company's own agent connect to TAI's MCP server and query your data with your permissions.
External agents read and, if you allow it, create and change records. Irreversible acts always stay with a person, on the platform or through Tali.
The agents, one by one
Each has its own page, with what it actually does.
Tali
The agent that runs the whole platform in conversation, with your confirmation.
Accounting agent
Closes the month for the firm's whole client base: invoices, taxes, bank, bookkeeping and delivery.
Finance agent
Bills to pay and receive, reconciled statement and the next 90 days of cash.
Agents inside processes
An agent at every step of the flow: reads, classifies, fills in and drafts.
Connect your agent
MCP to integrate ChatGPT, Claude, Gemini or your company's own agent.
Custom agent
What is specific to your industry, built inside the platform.
What you can ask for today
- Payroll: "Open September payroll, calculate it and show me the summary." Tali opens it, calculates and brings the totals for you to approve.
- Service desk: "Which tickets in my queue breach the SLA today?" The list arrives as a card, with a button to reply.
- Processes: "Build an expense reimbursement flow with manager and finance approval." Phases and fields are created after a single confirmation.
- Accounting firm: "What is missing to close client X's month?" The accounting agent answers step by step and points to the pending item.
- Finance: "What do I have to pay this week?" With the statement imported, suggested settlements already come matched.
- Files: "Generate Ana's payslip as PDF" or "import this employee spreadsheet". It reads and generates files right in the conversation.
Questions about the agents
Is this a chatbot?
Who approves what the AI does?
What does Tali not do?
Do the ready-made agents fit any company?
My team already uses ChatGPT. Can it see TAI data?
See an agent executing a real request from your company
In 30 minutes, with your structure on screen, Tali opens a process, answers about the operation and shows what it would do with your confirmation.