Product
What is Slimaco AI
Definition, positioning and value architecture — from company knowledge to work done.
Slimaco AI is an AI platform for organizations that captures company know-how and automates teams' repetitive work. Knowledge mining collects agreements, decisions and customer data from email, messaging and department systems such as CRM, ERP and helpdesk, and combines them into shared company knowledge. Agreements and decisions are added after a person approves them, while hard data, such as a customer's open tickets, updates continuously. AI agents work on that knowledge: they run tasks on demand or on a schedule in the apps the company already uses (Microsoft 365, Google Workspace and 1,000+ others), within permissions and human approval. The team uses that knowledge in the Slimaco assistant and soon also in ChatGPT, Claude, Gemini and Microsoft Copilot via MCP, always with the permissions of the person asking.
In practice, Slimaco takes over teams' repetitive work: it prepares replies to inquiries and quotes, reports, summaries, reminders and digests, updates data in connected systems and answers employees' questions. An agent is created from a plain-language description of the task — no coding and no drawing flows.
What sets Slimaco apart from general AI tools and automation is context. Agents work on how a specific company operates: its procedures, price lists, agreements and documents. When an area owner approves a rule change, the assistant and agents use the new version right away.
Slimaco's value doesn't come from owning one particular language model — the model is an interchangeable execution component. The more durable layer is the organization's knowledge, its agents and ways of working, permissions, integrations and decision history.
Three pillars of the platform
Agents and automations
Agents created from a task description work on demand or on a schedule, in Microsoft 365, Google Workspace and 1,000+ other apps, with human approval.
Slimaco assistant
Answers with sources, drafts of documents and messages, and web research when the answer isn't inside the company.
Company knowledge and knowledge mining
Approved, versioned knowledge with owners. Knowledge mining picks up new agreements from email, messaging and department systems and sends them for review.
Canonical positioning
Slimaco is an AI platform that automates teams' work in the context of the company: agents and the assistant work on the organization's approved knowledge, in its apps, with permissions, citations and human approval.
Product category: AI platform for organizations — agents, automations and an AI assistant working on company knowledge. Technical description: a model-neutral layer for knowledge, agent orchestration and governance for company AI systems.
What Slimaco is not
- It is not a wiki or a knowledge base like Notion or Confluence. Company knowledge is the foundation agents and the assistant work on, not the product itself.
- It is not a no-code tool for drawing flows. Automations are described in plain language.
- It is not its own foundation language model.
- It is not just a chatbot connected to a folder of documents or a simple RAG deployment.
- It is not a BI tool and does not replace a data warehouse or reporting platform.
- It does not replace expert accountability in legal, tax, compliance or security matters.
- It does not assume full AI autonomy — how independently agents act is set by policies, permissions and approvals.
The problem Slimaco solves
Companies grow faster than their ability to keep work organized. Knowledge stays in a few people's heads and in mailboxes, repetitive tasks are done by hand, and employees use AI each in their own way. Individual results come quickly, but no shared working standard or organizational memory emerges.
| Problem | Business impact | Slimaco's answer |
|---|---|---|
| Repetitive manual work | Your best people re-type data and prepare the same documents | Agents running tasks on demand or on a schedule |
| Knowledge locked in experts' heads | Constant interruptions for senior staff, risk of knowledge loss | Knowledge mining, approved knowledge and the Slimaco assistant |
| Scattered documents | Long search times and outdated versions in use | Sources, versions, semantic search, citations |
| Inconsistent AI use | Uneven output quality and Shadow AI | Shared assistants, skills, roles and rules |
| No content owner | Knowledge goes stale without control | Knowledge review, owners and gap signals |
| One-off automations | More silos and hard maintenance | One platform: shared knowledge, integrations and agents |
| Risky AI actions | No control over writes and communication | Permissions, human approval and a record of every action |
Value architecture — from knowledge to work done
The layers build on each other, but a client doesn't need to roll them all out at once. You can start with a single automation or with an assistant that answers the team's questions.
- Discovery and diagnosis (optional) — mapping processes, knowledge, risks, data and success metrics.
- Company knowledge — sources, versions, approval, access and knowledge mining.
- Slimaco assistant — questions, answers with sources, drafts, attachments and research.
- Assistants and skills — AI roles and repeatable ways of working described in plain language.
- Agents and automations — tasks on demand and on a schedule in connected apps.
- Governance — permissions, action approval, limits, audit and content security.
Deployment model
Slimaco AI runs primarily as a SaaS service, but the platform can also be deployed on-premise or in dedicated client infrastructure — both modes are available, and the exact model, processing region and way of integrating with AI models are agreed individually as part of the deployment conversation and contract.