AI Agents

AI agents that work for your business 24/7

Custom AI agents deployed on your website and connected to your CRM: qualifying leads, answering questions, booking appointments and publishing content while you sleep. No extra staff, no manual work.

An agent is only useful if it is trained on your business and wired into the systems you already use. A generic chatbot that cannot see your calendar or write to your CRM just annoys people politely.

Why most chatbots fail

The problem is not the model, it is the wiring

Almost every disappointing chatbot fails for the same two reasons, and neither is about which AI is behind it.

It does not know your business

Generic bots answer from generic knowledge. Ask about your pricing, your service area, your lead times or your process and it either invents something or deflects. An agent has to be grounded in your actual documents, and constrained to say it does not know rather than guess.

It cannot actually do anything

Most bots can only talk. They cannot check real availability, book the slot, create the CRM record or hand off to a person with context attached. So the visitor has a pleasant conversation and then still has to fill in a form. Nothing was saved.

The test I apply: can the agent complete the job end to end, or does it just collect information a human then has to re-enter? If it is the second, it has added a step rather than removed one.

What I build

Agents that do real work, not demos

Every agent is trained on your business and connected to the systems that matter.

✍

Blog posting agent

My most requested build. Researches topics in your industry, writes SEO-optimised articles and publishes them to WordPress on a schedule you set, with an approval step if you want one.

🤖

Lead qualification agent

Talks to visitors, asks your qualifying questions, scores against your criteria and only books calls with prospects who fit. Time-wasters get a polite, useful answer instead of your calendar.

📅

Appointment booking agent

Connects to Calendly, HubSpot Meetings or Google Calendar and books against real availability inside the conversation. No back-and-forth, no double bookings.

🎧

Customer support agent

Trained on your docs, FAQs and knowledge base. Handles tier-one questions instantly, escalates genuinely complex ones to a human with the conversation history attached.

📊

CRM push agent

Every conversation logged to your CRM with contact details, a summary, a lead score and a recommended next action. Your pipeline fills itself.

💬

Internal knowledge agents

An agent your own team can ask about your processes, documents and data, instead of hunting through folders or interrupting a colleague.

Setting expectations

What agents are good and bad at

Being clear about this upfront is why my builds tend to survive contact with real users.

TaskSuitabilityNotes
Answering documented questionsExcellentGrounded in your content, with a defined fallback when unsure
Qualifying and routing leadsExcellentConsistent criteria applied every time, unlike a tired human
Booking against real availabilityExcellentReliable once wired to the calendar API
Negotiating price or termsPoorShould hand to a human; never let an agent commit you
Handling angry or sensitive complaintsPoorDetect sentiment and escalate immediately with context
Giving regulated adviceNot appropriateLegal, medical and financial advice needs a qualified human

How I build them

From briefing to live on your site

01

Train on your data

Your website, docs, products, pricing and FAQs become the agent knowledge base, so answers come from your business rather than the internet.

02

Define the boundaries

Qualifying questions, scoring rules, escalation triggers and an explicit list of what it must never say or promise.

03

Connect your systems

Wired into your CRM and calendar so conversations become records and real bookings, not transcripts nobody reads.

04

Test against real questions

Run against actual enquiries you have received, including the awkward ones, before it speaks to a single customer.

05

Deploy and tune

Live on your site with transcripts reviewed weekly at first, and the agent tightened based on what people really ask.

Engagement

What an agent costs to build and run

Build cost

Fixed price after discovery. A focused agent such as lead qualification with calendar booking is typically one to two weeks. Multi-function agents with deep CRM integration run longer.

Running cost

Model usage billed by conversation volume, paid by you directly at cost with no markup. I size this during scoping and design prompts to keep per-conversation cost low.

Ongoing

30 days of tuning included, which matters more for agents than most builds because real users ask things you did not anticipate. Retainers available after that.

What I build agents with

OpenAI APIClaude APILangChainPythonVector searchn8nMake.comTwilioCalendlyHubSpotWebhooksOpenAI APIClaude APILangChainPythonVector searchn8nMake.comTwilioCalendlyHubSpotWebhooks

Common questions

AI agents, answered honestly

Not if it is built properly. Agents are grounded in your documents and instructed to say they do not know and offer a handoff rather than guess. I test specifically for this by asking questions your content does not answer, and check that it declines cleanly instead of inventing.
It books. The agent connects to your real calendar through Calendly, HubSpot Meetings or Google Calendar, sees genuine availability and confirms the slot inside the conversation. If it could only collect details, it would be a form with extra steps.
It escalates, with the full conversation attached so the human is not starting cold. You define the escalation triggers, and complaints or sensitive topics are routed to a person immediately by design rather than being attempted.
Yes, and they should. I build agents that identify themselves. Pretending to be human damages trust when people work it out, and they usually do. Being useful matters far more than pretending.
It depends on conversation length and the model chosen, but for typical lead-qualification conversations it is a very small amount each, and I design prompts to keep it that way. You get a projected monthly figure during scoping, based on your actual traffic.
Yes. Models handle major languages well out of the box. The limit is usually your source content, so if your documentation is only in English the agent will be strongest in English.
Conversations pass through the model provider API on tiers where data is not used for training, with retention configured. What is stored, where, and for how long is agreed before build. Sensitive fields can be redacted before anything is sent.
Prompts, qualifying questions and escalation rules live in configuration, not buried in code. You can adjust tone and questions yourself, and the documentation explains how. Bigger behavioural changes I handle on retainer.

Ready when you are

Put an agent on your website

Book a free call and I will tell you exactly what an agent could handle for your business, what it would cost per conversation, and where a human should stay in the loop.

Book a free 30-min call →