AI agent development

AI agents that do a defined job, safely

We build AI agents for specific, measurable tasks inside your existing systems, with clear limits on what they can do, evaluation before launch and a person in the loop for anything sensitive.

The problem

Why most AI agent projects stall

Demos are easy. Agents that act on real customer data, every day, without causing problems are much harder.

Impressive demos, unreliable production

An agent that works in a demo fails on messy real inputs and edge cases.

No guardrails

Agents are given broad access with no limits, approvals or audit trail.

No way to measure quality

Nobody can say how often the agent is right, so nobody trusts it.

Pilots that never ship

Experiments stay experiments because integration, security and monitoring were never planned.

Our approach

Narrow scope, real integration, measured quality

We start from one job worth automating, connect the agent to the systems it needs, and prove it works on real examples before it touches production.

What you get

  • One well-defined task per agent, with clear success criteria
  • Tools and permissions limited to what the task needs
  • Evaluation sets built from your real (anonymised) examples
  • Human approval for sensitive or irreversible actions
  • Logging of every run so decisions can be reviewed

Capabilities

What our AI Agent Development work covers

Pick one capability or combine several. Each is scoped, estimated and delivered with the same engineering standards.

Lead qualification agents

Read inbound enquiries, check fit against your criteria, enrich the record and route it to the right person.

Support triage agents

Classify and prioritise tickets, pull account context and draft replies for an agent to approve.

Document extraction

Turn invoices, contracts and forms into structured data with validation before it enters your systems.

Internal knowledge assistants

Answer staff questions from your own documents, with sources shown for every answer.

Guardrails and evaluation

Output validation, permission limits, test sets and regression checks for every change.

Model selection

The right model for each step, balancing quality, speed, cost and where data is processed.

In practice

Automation patterns we build

Business event, AI processing, system action, notification. Select an example to see how it runs.

  1. Leadform.submitted
  2. AI Agentqualify + enrich
  3. CRMdeal.created
  4. Slack#sales notified

How we work

How we deliver AI Agent Development

  1. Choose the job

    We pick one task with clear value and define what a correct result looks like.

  2. Design

    We specify inputs, tools, permissions, outputs and the human review points.

  3. Build and evaluate

    We build the agent and measure it against real examples until it meets the agreed bar.

  4. Launch and monitor

    We release in stages, review logs and improve based on real use.

Technology

Technology we use

Chosen for reliability, maintainability and fit with your existing stack.

Models

  • OpenAI
  • Anthropic Claude
  • Open-weight models

Agent tooling

  • n8n AI agents
  • LangChain
  • Model Context Protocol (MCP)

Data

  • PostgreSQL
  • pgvector
  • Vector databases

Integration

  • Node.js
  • Python
  • REST & webhooks
  • HubSpot
  • Zendesk

Use cases

Where teams put this to work

Common starting points. Your process will have its own details, which is why every engagement starts with discovery.

  1. 01

    Inbound lead qualification

    Every enquiry answered quickly, scored against your criteria and routed with context.

  2. 02

    Ticket triage and drafting

    Support agents start from a classified ticket and a suggested reply.

  3. 03

    Invoice processing

    Supplier invoices read, validated and prepared for approval in your accounting system.

  4. 04

    Contract review support

    Key clauses and dates extracted for a person to check.

  5. 05

    Internal policy assistant

    Staff get answers from your handbooks with links to the source.

  6. 06

    Data clean-up

    CRM records standardised and de-duplicated with changes queued for review.

Industries

Built for operational teams across industries

The patterns carry across sectors. What changes is the data, the systems and the rules, and we learn those first.

  • SaaS & technology

    Product engineering, integrations and AI features for software companies.

  • Professional services

    Automated intake, document workflows and client reporting for agencies, consultancies and firms.

  • Finance operations

    Invoice processing, reconciliation support and reporting automation.

  • Real estate

    Lead handling, listings and transaction workflows for brokerages and property teams.

  • E-commerce & retail

    Order, inventory and customer-service automation connected to your store and ERP.

FAQ

AI Agent Development questions

Straight answers to the questions that come up in first calls.

Ask us directly
What is the difference between an AI agent and a workflow automation?

A workflow follows fixed steps you define. An AI agent decides which steps or tools to use to reach a goal. Many good solutions combine both: a predictable workflow with an AI step only where judgement or language understanding is needed.

How do you stop an AI agent making harmful mistakes?

We limit what it can access and do, validate its outputs, require human approval for sensitive actions, and log every run. We also measure it against real examples before launch and after every change.

Which AI model will you use?

It depends on the task, the data and where it may be processed. We often use different models for different steps, and we can design for providers or regions that fit your data requirements.

Can the agent work inside our existing tools?

Yes. Agents usually run behind the tools your team already uses, such as your CRM, help desk, inbox or Slack, rather than in a new app.

Related services

Most engagements touch more than one discipline. The same team can take you from strategy to production.

01

AI & Automation

AI agents and workflow automation that remove manual work across your tools.

  • AI agents
  • n8n, Zapier & Make
  • CRM automation
  • AI integrations
02

n8n Automation

n8n workflows, self-hosting and migrations from Zapier or Make, built and maintained for you.

  • n8n workflows
  • Self-hosted n8n
  • Zapier & Make migration
  • AI agent nodes
03

AI Chatbot Development

AI chatbots for your website, WhatsApp or help desk that answer from your own content.

  • Website chatbots
  • WhatsApp & Slack bots
  • Answers from your content
  • Human handover

Start a project

Tell us what is slowing your team down

Share the workflow, product or team challenge. We will come back with a clear recommendation and next steps.

Intro call · Fixed-scope proposal · No obligation