AI agents & automation
Agents that act inside your systems, with you approving
We build agents that read, decide and act across your ERP, email, CRM and WhatsApp, orchestrated with tools like LangGraph, MCP and n8n. A human approves every step that matters.
Discuss AI agents & automation for your teamWhat we build
Automation you can trust.
- 01Multi-step agents with tool use
- 02MCP connectors to your internal systems
- 03Human-in-the-loop approvals
- 04WhatsApp and email automation
- 05Scheduling, quoting and follow-up agents
- 06Logging, replay and safety limits
Use cases
Asked often.
A chatbot answers questions, while an agent takes actions: it reads an email, checks your ERP, drafts a quote, updates the CRM or sends a WhatsApp follow-up. Agents run multi-step tasks using tools connected to your systems through MCP connectors and orchestration tools such as LangGraph and n8n. Because they act, they need guardrails, logging and approvals that a simple chatbot does not. If you only need answers from documents, RAG is usually enough.
Agents fit repetitive, rule-heavy work that moves data between systems, such as quote and tender preparation, purchase orders, lead follow-up and back-office data entry. They are a poor fit for decisions that need judgement with little data, or for processes nobody has written down yet. We start by mapping the workflow with the people who run it and automate only the steps worth automating. Anything that sends, pays or changes important records goes to a person for approval.
Through the APIs those systems already expose, wrapped as tools the agent is allowed to call. We build MCP connectors to internal systems such as ERPNext, Odoo, Zoho or a custom platform, and use n8n or LangGraph to orchestrate the steps. Integration starts by deciding which system owns which record, so the agent writes to the right place. Each tool has clear limits, and every action is logged so it can be reviewed and replayed.
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