AI assistants for employees
They answer questions, help draft a task, prepare a document, find the right regulation and keep context from being lost between departments.
Enterprise platform
Platform AI brings AI into the business without scattered chats and hand-built integrations: agents work with tasks, documents, processes, roles and the corporate knowledge base.

The agent identifies the type of enquiry and the data it needs.
It uses the knowledge base, the history, documents and internal rules.
Tasks created, roles assigned, SLA control switched on.
AI for business stops being a window you copy things out of. It runs as a layer over the systems you already have — agents read your data, move your processes and leave a trace where your team works.
Use cases
AI is not there for the experiment. It is there to speed up specific operations: take out manual routing, cut the time spent hunting for information, and make the team’s work visible.
They answer questions, help draft a task, prepare a document, find the right regulation and keep context from being lost between departments.
They run on events and on a schedule: check incoming requests, start BPMN routes, escalate overdue items and record the history.
It brings documents, tasks, requirements and decisions together, so AI answers from company data rather than from whatever context it found outside.
It helps classify documents, check they are complete, draft replies and hand tasks to the people responsible.
It collects statuses, deadlines, owners and bottlenecks, so a manager sees what the processes actually look like.
Start from a cloud workspace, assemble the first scenario and check what AI is worth on real business tasks.
Why it works here
Agents are wired to roles, processes, forms and tasks — so the work never leaves the system it belongs to, and nobody copies data between windows.
Four steps from a single process to a measured effect.
Start with one process
Incoming requests, document approvals, a knowledge base, SLA control or drafting replies to customers — one process you can measure.
Get your own cloud instance of Platform AI and try the scenario in a safe sandbox before anything touches production.
Set up access, forms, workspaces, regulations and the knowledge sources your AI agents are allowed to read.
Watch statuses, deadlines, requests, agent actions and how the process converts — then scale what worked.

It is artificial intelligence applied to a company’s working processes: assistants, agents, routine automation, data analysis, task control and support for employees.
A chatbot answers a question. An agent can act on an event, take a task, use data, change a status, start a route and hand the result to whoever is responsible.
Yes — when it runs inside a corporate platform with roles, action logs, limits on the data it can reach and clear rules for how processes execute.
With one measurable process: requests, documents, a knowledge base, approvals or support. Once the effect is clear, the scenario can be scaled.