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AIAai automation services

AI automation services with a person at every gate that matters.

Founcy Solutions' AI automation services focus on three marketing workflows where automation genuinely pays: content operations, reporting and lead routing. Each one is designed with human review checkpoints, a map of where your data goes, and a baseline measured before we start, so you can see the time saved instead of taking it on faith.

Find my first workflow → What we won't automate
  • human review built in
  • data flow mapped
  • measured against a baseline
workflow.runsillustration
  • content ops: decay alert → data → AI brief → editor review → writer
  • reporting: scheduled pull → AI summary → analyst check → send
  • lead routing: enrich → classify → spot-check → assign owner
human gate in every laneaudit log per runexample workflows
definition

What are AI automation services?

AI automation services design and build workflows where software, including large language models, takes over repetitive steps in a business process: pulling data, drafting first versions, classifying requests, routing work and flagging anomalies. The useful version is not a chatbot bolted onto a team. It is a mapped workflow with clear inputs, validation rules, a person reviewing anything high-impact, and logs that show what ran, what changed and how much time it saved against the old way of working.

Lanes
Content operations, reporting and lead routing
People
Review anything published, client-facing or high-impact
Data
Mapped per workflow; sensitive fields excluded or masked
Proof
Time saved and accuracy, measured against a pre-automation baseline
sound familiar?

Busywork with a clear pattern.

Tap what describes your team. These become the shortlist for your first pilot.

Tap anything that sounds familiar.

three lanes

AI workflow automation where it earns its keep.

We stay in three lanes we know well from running search programs. Each one shows what the automation does and where a person stays in charge.

01 · content ops

Briefs, links and decay alerts

  • SERP-informed content briefs
  • Internal-link suggestions
  • Schema drafts for new pages
  • Alerts when pages start losing clicks

Human gate Editors approve every brief and every word. Nothing publishes automatically.

02 · reporting

Data pulled, anomalies flagged

  • Search Console, GA4 and CRM pulled by API
  • Anomaly detection on key pages and queries
  • Plain-English summaries with sources
  • Dashboards that update themselves

Human gate An analyst checks the numbers and the narrative before anything is sent.

03 · lead routing

From form to owner, fast

  • Enrichment and de-duplication
  • Request classification and scoring
  • CRM owner assignment by your rules
  • Alerts with context for the rep

Human gate Low-confidence classifications go to a person, and every decision is logged.

// every engagement includes
Workflow audit, ranked by valueBlueprint with review checkpointsPilot measured against a baselineCRM, analytics & CMS integrationsVersioned prompt libraryMonitoring, alerts & audit logsTraining & runbooksTime-saved & accuracy reporting
every automation service

Pick the job you want off your plate.

Fourteen focused services, each with a person reviewing the steps that matter.

AGT

AI Agent Development

Agents that research, draft and act inside your tools, with approval steps.

Explore → BOT

AI Chatbot Development

Website and support chatbots trained on your own content.

Explore → VOX

AI Voice Agents

Phone agents that answer, qualify and book, then hand over to a person.

Explore → BPA

AI Business Process Automation

Repetitive back-office work moved to checked, logged automations.

Explore → GHL

GoHighLevel CRM Setup

Pipelines, calendars and contacts set up around how you sell.

Explore → GHA

GoHighLevel Automation

Follow-ups, reminders and nurture sequences inside GoHighLevel.

Explore → GHF

GoHighLevel Funnels

Landing pages and funnels built and tracked in GoHighLevel.

Explore → CRM

CRM Automation

Leads routed, enriched and followed up in the CRM you already use.

Explore → LGA

Lead Generation Automation

Capture, qualify and route enquiries the moment they arrive.

Explore → N8N

n8n Automation

Workflows built in n8n, self-hosted or cloud, documented and owned by you.

Explore → WFL

Custom Workflow Automation

Bespoke automations where off-the-shelf tools fall short.

Explore → INT

API Integration Services

Connect the apps you already pay for so data stops being re-typed.

Explore → WAP

WhatsApp Automation

Opt-in WhatsApp replies, reminders and updates on the official platform.

Explore → EML

Email Automation

Welcome, follow-up and reminder emails that land in the inbox.

Explore →
guardrails

What we won't automate.

We publish this list on purpose. A partner who can't tell you what they won't automate hasn't thought hard about what can go wrong.

Publishing at scale

No pages generated in bulk and pushed live. Google's spam policies treat scaled content made to manipulate rankings as abuse, however it's produced.

Unread customer messages

Emails, replies and reports that reach your customers are read by a person before they go.

Strategy and priorities

A model can summarise the data. Deciding what to do about it stays with your team and ours.

Expert sign-off

Claims, numbers and advice in expert content are signed off by someone qualified, especially on health, finance or legal topics.

Anything legally binding

Pricing, contracts and commitments to customers are never drafted and sent without a person in charge.

Unmapped sensitive data

If we can't say where a field goes and how long it's kept, it doesn't go into a model.

built to be trusted

AI tool sprawl, or a working system?

Most teams already have the tools. What's missing is the workflow design around them.

governance: none
Starting pointBuy tools, then look for usesMap the workflow first and automate its most expensive steps
ReviewOutputs go straight outHuman checkpoints on anything published, client-facing or high-impact
ContentPages generated in bulkBriefs and drafts for editors; nothing mass-published
DataPasted into whichever chatbot is openData flow mapped, sensitive fields excluded, vendor terms reviewed
ErrorsNoticed when someone complainsValidation rules, alerts and audit logs on every run
Results"It feels faster"Time saved and accuracy measured against a baseline
how it works

One pilot first. Then the next.

Starting small keeps the first phase measurable, and makes the case for the second one with your own numbers.

  1. 01

    Discover

    We map current workflows, data sources and constraints, and time the steps to set a baseline.

    → ranked automation candidates
  2. 02

    Design

    Pick the workflow, define human checkpoints, data handling, validation rules and success metrics.

    → automation blueprint
  3. 03

    Pilot

    Build it, test it against real cases from your history, and measure it against the baseline.

    → pilot results report
  4. 04

    Roll out

    Integrate fully, document every step and train the people who own the checkpoints.

    → runbooks and training
  5. 05

    Optimise

    Monitor accuracy and running cost, refine prompts and rules, then pick the next workflow.

    → monthly accuracy and cost review
stack

Tools chosen per workflow.

Models and vendors are picked for each job based on data sensitivity, accuracy and running cost.

// orchestration
n8nMakeZapierWebhooks & APIs
// models
OpenAIAnthropicGoogle GeminiRetrieval (RAG) where needed
// data
Search Console APIGA4 APIBigQueryLooker Studio
// systems
HubSpotSalesforceSlackMicrosoft TeamsYour CMS
what drives the cost

What does AI automation cost?

Build cost and running cost are different things. These four drivers shape the build; API usage and tool licences are estimated separately.

Workflows

Each workflow needs its own design, testing and checkpoints.

Integrations

Clean APIs are quick; legacy systems and warehouses take longer.

Review & compliance

Client-facing or regulated outputs need stricter checks and logging.

After launch

Models, prompts and APIs change, so someone has to watch accuracy.

keep exploring

Related services.

CXO

Customer experience optimisation

Fix the journey the routed lead took before it reached the form.

Explore → ENT

Enterprise development support

Engineering capacity for integrations inside larger stacks.

Explore → SUP

Website support & management

Ongoing care that watches search health, not just uptime.

Explore → GEO

AI SEO / GEO

Get your brand cited in ChatGPT, Perplexity, Claude and Gemini.

Explore →
faq

AI automation questions.

It removes repetitive steps such as data pulls, first drafts, categorisation and routing, and surfaces anomalies sooner than a person scanning dashboards. Judgement calls, including strategy, final edits and client communication, stay with people.
Google's guidance targets low-value content made mainly to manipulate rankings, including scaled content abuse, rather than the use of AI itself. AI-assisted drafts that subject experts review and improve are a very different thing from pages mass-published without oversight, which is why we never automate publishing.
Data handling is designed per workflow: which tools touch which fields, retention and training settings, and which sensitive fields are excluded or masked. We document it and ask your security or legal team to review vendor terms before rollout.
It depends on integration complexity, data quality and how many approval steps the workflow needs. Starting with a single pilot keeps the first phase short and measurable, and gives you real numbers before committing to more.
Build cost depends on the number and complexity of workflows, integrations and review requirements. Running cost, meaning model API usage and tool licences, is estimated separately so you can see the true monthly cost against the time saved.
Workflows include validation rules, human checkpoints for high-impact outputs, error alerts and logs, so mistakes are caught before they reach anyone and can be traced and fixed afterwards. Accuracy is reviewed as part of ongoing monitoring.
We choose per workflow, based on accuracy for the task, data-handling terms and running cost. That can mean models from OpenAI, Anthropic or Google, or no model at all where simple rules do the job more reliably.
start with one workflow

Which hour of busywork goes first?

Send your domain and tell us where the hours go. We'll come back with the workflow worth piloting first, and the checkpoints it needs.

https://

quote within 24 hours · humans in the loop · no hype, just measured hours