Workspace Intelligence: AI does the groundwork, people make the decisions that matter most

Workspace Intelligence is a way of working in which AI lives inside the collaboration tools your team already uses, learns how your company does things, does the work before you ask, and leaves the most important judgments to people. ANIMA is an enterprise AI that works this way.

(The scenario and numbers below are illustrative.) It is 9 AM on Wednesday and you are a sales manager. Before you have said a word, three things are already ready:

• Last week's sales report, already posted in the team group.
• Next month's purchasing recommendations, already compiled.
• The month-end statement has been checked; ANIMA sends it to the client only after you press Confirm.

From “ask AI” to “AI gets started”

For the past two years, most people have opened ChatGPT to ask a question, then copied the answer back into the original file or group. Workspace Intelligence reverses that order: ANIMA joins groups and channels as a team member, and wherever the work happens, it is there.

No SOP needed up front: it learns from everyday collaboration

SOPs (standard operating procedures) get written and then nobody follows them, and the good practices of senior colleagues are often known only to them.

ANIMA learns how things are done from three sources:

• Learning automatically: it builds up knowledge continuously from existing conversations, documents, and everyday collaboration.
• Built by the team: describe a workflow in text or upload an existing SOP, and a workflow is created.
• Industry templates: common workflows for your industry can be applied on the day of rollout.

ANIMA's memory covers three levels: individual, team, and company. An individual's way of working gradually becomes the team's and the company's, and when people move on, the company's way of working stays. A newly learned practice is enabled only after the responsible colleague confirms it.

No need to ask: ANIMA takes it from here

The weekly report at 9 AM started because the scheduled time arrived. The moments when ANIMA starts work are called triggers, and they fall into roughly three kinds:

• Someone calls on it: it's mentioned, or a task is assigned to it.
• The time comes: the weekly report, month-end close, tomorrow's meeting.
• A system changes: a notification arrives, or the previous step finishes.

The last two need no one to ask.

Once work comes in, the orchestration hub decides two things: who gets it, and which one goes first. Take the three 9 o'clock items as an example:

• Weekly sales report: handed to the weekly report workflow, which produces it when the scheduled time arrives.
• Purchasing suggestions: handed to an agent (an AI that can carry out tasks itself), which estimates demand from past shipping cycles and customers' ordering patterns.
• Statements: once the agent finishes checking, you decide whether they go out.

When several jobs are waiting at once, ANIMA sets the order using the team's goals and priorities held in memory.

What do you confirm? Anything that sends a message outside the company or writes to a system goes through you first; internal preparation and notifications are simply completed. Of the three 9 AM items, the weekly report and purchasing suggestions are internal preparation, so they are completed directly. The statement sent to a customer is a message leaving the company, so it waits for your confirmation.

ANIMA doesn't just follow the steps; it can improve them

In every run, ANIMA looks for the points in a workflow where people re-check things repeatedly, redo work, or wait on a blocker. For example, if statements always stall while waiting for a manager's sign-off, ANIMA flags that step and suggests a change.

Suggested improvements are graded by impact. Low-risk adjustments are verified against run results and then applied. Larger changes become the new version of the workflow only after the responsible team member confirms them.

The more work agents take on, the fewer steps each run uses, and AI usage costs come down with them. (Illustrative) A workflow that started with eight steps is trimmed to five, and the number of times you need to confirm drops from three to one. The longer it runs, the less often you need to step in.

What makes this work is company context

ANIMA can start work because of company context: the company's workflows, rules, customer preferences, and the background behind each decision. ANIMA builds it with an index, process mining, a knowledge base, and memory.

The architecture has four layers, from the bottom up:

• Data and company context
• Agents
• Workflows
• Orchestration hub: assigns and orders the work

ANIMA keeps the access permissions each data source already has. The workflows, skills, and knowledge it learns belong to your company, and they all carry over if the underlying model is swapped.

Book a free 30-minute call and bring a document your team handles every week, such as a weekly report or a statement. We'll look together at what ANIMA could do for your team.