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AI agents that take the work off your team

Autonomous AI agents that qualify leads, run first-level support, process invoices and drive onboarding flows — plugged into the tools you already use. Shipped with guardrails, monitoring and a human escalation path.

Four agent patterns that work

Sales qualification agent

Reads every inbound form and email, asks clarifying questions, enriches company data, scores the lead, books a call in the right rep’s calendar and writes the record into the CRM. Hands off to a human when the deal is large enough.

Typical stack: HubSpot, Pipedrive, Calendly, Clearbit, Slack.

Level-1 support agent

Resolves standard tickets end-to-end: order status, returns, invoice copies, password resets. Grounded in your own help centre. Escalates cleanly with full conversation context to a human for anything outside its playbook.

Typical stack: Zendesk, Intercom, Shopify, SAP.

Invoice & document agent

Receives invoices, contracts and shipping documents by email. Extracts structured data, matches against purchase orders, flags anomalies, routes approvals and books into DATEV, lexoffice or your ERP.

Typical stack: DATEV, lexoffice, SAP Business One, Microsoft Dynamics.

Onboarding & research agent

Walks new customers through multi-step onboarding, pulls reference data from public sources, writes personalised welcome sequences, and surfaces accounts at churn risk to your customer success team.

Typical stack: Brevo, Mailchimp, HubSpot, Notion, PocketBase.

Built so you can actually trust it

Explicit permissions

Every tool an agent can call is declared and reviewed. No open-ended internet access unless the use case demands it.

Golden-dataset evaluation

Before go-live we build a representative test set and measure accuracy, refusal rate and hallucination rate.

Kill-switch & audit log

A real, tested stop mechanism. Every agent decision is logged, traceable and exportable for compliance.

Frequently asked questions

What is the difference between an AI agent and a chatbot?

A chatbot answers questions in a conversation. An AI agent takes action: it opens tickets, writes into a CRM, sends emails, calls APIs. It can chain multiple steps autonomously until a task is done.

Where do AI agents deliver the fastest ROI?

Repetitive, rule-heavy tasks with structured data: lead qualification, L1 customer support, invoice processing, onboarding workflows. These typically pay back within a single quarter.

How do you keep agents from going off-script?

Every agent runs with explicit tool permissions, input/output validation, a dry-run mode, audit logs and a human-in-the-loop for financial or customer-facing actions until trust is earned.

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