Practice 03 of 06 — AI · Newest line

AI agents and data infrastructure that do the work, not just report on it.

We build automation, AI agents and analytics on top of the tools your team already uses — so the win isn't a dashboard nobody opens, it's hours given back every week.

Engagement length · 4–6 weeks for first build Format · Project-based or retainer Works alongside · Marketing, IT & Business practices

What this practice covers

From "we have data" to "the data does something."

Most businesses we meet already have data — in a CRM, a WooCommerce store, a folder of spreadsheets. What's usually missing is the layer that turns that data into automated action: a follow-up that sends itself, a report that builds itself, a query that answers itself.

The AI & Data Consulting practice exists to build that layer — scoped to the workflows that actually cost your team time today, not a speculative "AI strategy" with no shipped output.

Where this practice plugs in

01HospitalityRevenue & booking automation

02MarketingReporting & campaign data

03IT & SoftwareSitting on top of existing stack

04Business ConsultingDecision-grade dashboards

What you get

Five ways we plug AI into a business.

01 · AUDIT

AI Readiness & Opportunity Audit

A short audit of your current tools and workflows that identifies which 2–3 automations would save the most time first — before any build starts.

02 · AGENTS

AI Agents & Workflow Automation

Purpose-built agents for repetitive operational work — reporting, lead follow-up, content drafts, order or booking workflows.

03 · DATA

Data Infrastructure & BI Dashboards

Getting scattered data into one place and building dashboards that decision-makers actually open, instead of static monthly exports.

04 · FORECASTING

Predictive Analytics & Forecasting

Demand, revenue or booking forecasts built from your own historical data — sized to be useful for planning, not just descriptive.

05 · SUPPORT AI

Conversational AI & Support Automation

First-line chat and query handling that resolves the repetitive questions, and routes the rest to your team with full context attached.

06 · TRAINING

Team Enablement

Documentation and hands-on training so your team can run, adjust and extend the automation after we hand it over — not depend on us forever.

How it runs

The same four-stage process, applied to AI.

Discover

Map your current tools, data sources and the three most time-consuming repetitive workflows.

Design

Architect the agent or dashboard around your real systems — no rip-and-replace of tools that already work.

Deploy

Ship the first automation live, with your team using it inside the first build cycle, not after a long pilot.

Drive

Track hours saved and accuracy, then expand to the next workflow once the first one is proven.

Frequently asked

Before you book a call.

Do we need a data team before working with you?+

No. Most clients start with spreadsheets and a handful of disconnected tools. Part of the engagement is building the minimum data infrastructure needed before automation makes sense.

What kind of tasks can actually be automated?+

Repetitive, rules-based work is the best starting point — reporting, follow-ups, lead routing, content drafts and first-pass customer queries. We typically start with one workflow and expand from there.

Will this replace our existing software?+

Usually not. AI agents and automations are built to sit on top of the tools you already use — your CRM, helpdesk, spreadsheets or WordPress site — rather than replace them.

How long does a typical engagement take?+

An initial audit and first automation usually ships within four to six weeks. Larger data infrastructure or multi-agent builds run longer, scoped during discovery.