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AI Agents & Agentic
Workflow Development

We build autonomous AI agents that think, plan, and act across multi-step tasks — without a human in the loop for every decision. Powered by LangGraph and our Open Claw platform.

Build an agent

What makes an agent different

Automation that reasons,
not just executes.

Traditional automation follows fixed rules. If X happens, do Y. Reliable — but brittle. It breaks the moment reality doesn't match the script.

An AI agent is different. It reasons about a goal, plans a sequence of steps, executes tools and APIs, interprets the results, and adjusts its approach — all without a human managing each decision.

The distinction LangGraph draws is precise: a workflow is a defined graph of steps. An agent uses an LLM to decide which steps to take next. Both have their place. We build both — and we know when each is the right choice.

Workflow vs Agent

Fixed workflows

Predictable, auditable, fast. Best for well-defined, repetitive processes with low variance.

AI agents

Flexible, adaptive, capable of novel situations. Best for tasks that require interpretation, judgment, or multi-step reasoning.

Multi-agent systems

Multiple specialised agents collaborating — each handles a domain, one orchestrates. Used for complex, parallel workloads.

Our platforms

Built on Open Claw and Hermes.

We build agentic systems on top of two platforms we develop and maintain ourselves — giving us deep control over agent behaviour, memory, and deployment.

Platform

Open Claw

Open Claw is our agentic workflow platform that lets businesses interact with autonomous agents through chat interfaces including WhatsApp, web chat, and email. It's designed for real-world tasks — not demos.

Chat-based task execution (WhatsApp, web, email)

Multi-step agentic workflows triggered by natural language

Integration with your existing business tools and APIs

Agent framework

Hermes Agent

Hermes is our agent framework built for persistence, memory, and long-running tasks. It supports scheduled automations, subagent orchestration, sandboxed execution, and multi-channel usage — designed for production deployment.

Persistent memory across sessions and tasks

Scheduled automations and background task execution

Subagent orchestration for complex parallel workflows

Use cases

What AI agents can do for your business.

Customer service agents

An agent that handles enquiries, qualifies leads, books appointments, and escalates to humans only when needed.

Research and analysis agents

Agents that browse the web, gather data, synthesise findings, and produce structured reports on demand.

Internal operations agents

Agents that query your systems, generate reports, update records, and notify teams — running on a schedule or triggered by events.

Document processing agents

Agents that read, extract, classify, and route documents — invoices, contracts, forms — without human review at every step.

Outreach and follow-up agents

Personalised outreach sequences, follow-up messages, and lead nurturing — executed by an agent that adapts based on responses.

Integration orchestration agents

Agents that sit across multiple systems and keep data in sync, trigger downstream actions, and handle exceptions automatically.

Learn more

Want to understand AI agents better?

Our blog covers what AI agents are, how they differ from traditional workflows, and when to use each. Practical guides written for business owners, not engineers.

Read the blog

Ready to build an agent?

Tell us about the task you want to automate. We'll design an agent that handles it — reliably, at scale.

Start a project See Business Automation