How Klart AI Works

Agents

A Klart AI agent is an AI employee scoped to a specific role — a support lead, an HR assistant, a sales analyst. Instead of a general-purpose chatbot, each agent is configured with the sources it’s allowed to read, the actions it’s allowed to take, and the tone it should answer in. Teams typically start from one of Klart AI’s named agents or build a custom one for a role that doesn’t fit an existing template — see Klart Agents.

The Custom Agent Builder

Most platforms make you configure an agent by hand. Klart AI does it for you: at signup, the Automated Custom Agent Builder reads the role you describe, your company data, and your toolstack, then assembles a specialist that’s already scoped to your business — no prompt engineering or workflow scripting required. You review its first output, approve it, and it runs from there. Tone, permissions, and autonomy can all be adjusted afterwards.

Klart Brain

Klart Brain is the persistent memory and retrieval layer behind every agent. It grounds each answer in your verified company data — documents, tickets, records, wikis — rather than generating from general knowledge alone, and it retains context across tools and time as it’s used. In practice this means:

• Answers are grounded in the sources you’ve authorized, not invented.
• Responses can cite the document, ticket, or record they came from.
• An agent that doesn’t know the answer says so, instead of guessing.

The Autonomy Engine

Autonomy without oversight is a liability, so every agent is paired with the Autonomy Engine — the permission layer that decides exactly what it can read, draft, and decide on its own. Agents inherit your existing access rules rather than getting a separate set of permissions, every action is logged with context for audit and compliance, and nothing is used to train models outside your workspace. See Security for the full picture, including certifications and data-handling practices.

Automations

Beyond answering questions, agents can run recurring or event-driven work described in plain language — a daily digest, a weekly report, a multi-step workflow across connected tools. Each automation is grounded in Klart Brain the same way a conversational answer is, so scheduled work acts on real, current data rather than a stale snapshot.

Model routing

Klart AI is not tied to a single model provider. Each task is routed to the model best suited for it — across providers such as OpenAI, Anthropic’s Claude, and Mistral — under one consistent set of governance, sourcing, and reliability rules. This is handled automatically and isn’t something you configure per request.

Where agents show up

Agents are deployed once and reused everywhere your team already works: the Klart AI dashboard, Slack, Microsoft Teams, an embeddable website widget, WhatsApp, and email. The chat API documented here is the same underlying capability, exposed directly over HTTP so you can bring it into your own product or internal tooling.