Introducing yeos: AI Agents That Actually Do the Work

For the last two years, “AI” in the enterprise has mostly meant chat. Ask a question, get a paragraph. Useful, but limited. The moment you want the AI to actually do something — pull the latest project status, update a Jira ticket, check a contract against your policies, or route an HR request — you hit a wall.

That gap between “answers” and “actions” is exactly what yeos is built to close.

The chat trap

Chatbots are great at summarizing and brainstorming. But they live outside your systems. They don’t know your documents, your tools, or your approval flows. Every answer becomes a starting point for manual work: copy the suggestion, open another tab, find the right system, paste it in, hope nothing got lost in translation.

Worse, generic AI tools often can’t tell you where an answer came from. For compliance, finance, legal, and healthcare teams, that is a non-starter.

What “doing the work” means

yeos agents are designed to operate inside your existing workflow. They read your documents, connect to your tools, and take action — all with full traceability. Instead of asking “What is our vacation policy?” you can ask “Approve Sarah’s vacation request if it complies with policy and notify payroll.”

A few things that set yeos agents apart:

• Source-backed answers: every response cites the documents it used.
• Tool integration: connect Jira, Salesforce, SharePoint, APIs, and custom tools via OpenAPI.
• Role-based access: control who can run which agent and see which documents.
• Swiss hosting: your data stays in Switzerland, with GDPR and DSG compliance built in.

How yeos agents are built

Building an agent in yeos starts with knowledge. Upload PDFs, Word documents, spreadsheets, or connect a document source. The platform chunks, indexes, and embeds the content so the agent can retrieve exact passages on demand.

Next, you define what the agent can do. A simple prompt shapes its personality and scope. Then you attach tools: search the knowledge base, fetch a full document section, call an external API, or execute code in a sandbox.

Finally, you share the agent with your team. Everyone works from the same source of truth, with audit logs showing exactly what was asked, what sources were used, and what actions were taken.

Built for teams that can’t afford to guess

Project management teams use yeos to generate status reports from scattered documents. HR teams answer policy questions with citations. Support teams triage tickets and draft responses grounded in the knowledge base. Legal and compliance teams review contracts and flag risks against internal playbooks.

In every case, the agent is not just producing text. It is reading, deciding, and acting — under the guardrails you set.

Start with one workflow

You do not need to automate everything on day one. Pick one repetitive workflow — a weekly report, a policy Q&A, a contract check — and build an agent for it. Most teams have their first useful agent running within an hour.

AI that chats is nice. AI that works is better.