AI agents

Custom AI agents for your tasks

On d8n.ai you can build any custom AI agent for your company’s tasks — not only the ready-made role agents. We do it with a proven methodology: first map the process, formalize it, design the agent’s actions, and fix success criteria before development.

For your processesA methodology, not “bolt-on AI”Success criteria up front

Why methodology matters

Most enterprise AI projects fail to deliver not because of the models but because of the approach: the agent is placed beside the work. Per McKinsey, AI leaders are 2.8× more likely to fundamentally redesign workflows rather than automate point tasks. So we start with the process, not the agent.

How we build an agent

Four steps — from understanding today’s work to a measurable result.

1

Process AS-IS

Map how the work is done today: steps, participants, systems (CRM, ECM, data) and pain points. Agent-driven workflows can’t be built without a granular understanding of the current process — McKinsey’s first step too.

2

Formalize the process

Redesign the process for human–agent collaboration rather than bolting AI onto the old one. The goal is reinvention, not automating inefficiency.

3

Agent actions

Define exactly what the agent does: inputs, expected outputs, steps — and where the decision stays with a human. Clear inputs/outputs and approval points are the basis of a reliable agent.

4

Success criteria

Fix measurable success criteria before building — e.g. “resolve 60% of tier-one tickets without escalation at 95% satisfaction” — and evaluate the agent on your real documents, tools and policies, not abstract tests.

Methodology sources: McKinsey — redesigning workflows for agents · McKinsey — agentic AI advantage · Stanford HAI — agentic AI

What can be built

Industry-specific agent

For the specifics of your industry and company not covered by ready solutions.

Policy-driven agent

An agent that runs a specific process or policy by your rules.

Integration agent

Works with your systems (ERP, CRM, HRM) via connectors and MCP.

Analytics agent

Gathers data, briefings and reports on your processes and metrics.

Multi-agent flow

An orchestrator routes tasks to specialist agents with explicit inputs and outputs.

Any process you have

If a process can be described, it can be automated on d8n.ai.

How to engage

Development is led by our solutions engineers. Custom agents can be built under an Unlimited Services package (PBU) — a yearly package that automates any process without programming.

Tell us which agent you need

Describe the process and task — our solutions engineers will propose how to build the agent on d8n.ai.

Get a demo