AI automation that takes the repeat work off your team
Foundreco builds automations in n8n, Zapier, Make and GoHighLevel, adds AI steps on OpenAI, Claude or Gemini where they earn their place, and builds AI call and voice agents on Vapi and Retell. Scoped after a free audit, fixed price, and handed over working.
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What is AI automation, and what does Foundreco build?
AI automation connects the tools a business already uses so that repeated work runs on its own, with an AI model handling the steps that need judgement: writing, summarising, classifying or answering. Foundreco builds these systems in n8n, Zapier, Make and GoHighLevel, and builds AI call and voice agents on Vapi and Retell AI. The eight projects on this page ranged from $200 to $2,500 and from one day to a month.
Most of what gets called automation is not clever. It is a form submission that should create a CRM contact, a booking that should send a reminder, an order that should be checked for duplicates before anyone touches it. The AI part matters in a minority of steps, and a good build is honest about which ones. A rule that never changes should be a rule, not a prompt.
What can be automated?
| Type | What it looks like in practice | Usually connected to |
|---|---|---|
| CRM workflows | Leads move through pipeline stages on their own; a status change triggers the right SMS or email | GoHighLevel, HubSpot, Salesforce, Zoho |
| Lead generation | Form to CRM to follow-up sequence, with enrichment and routing by tag or tier | Typeform, JotForm, your website, HubSpot, Apollo |
| Email automation | Sequences, reminders and post-visit follow-ups that stop when the person replies | Gmail, Mailchimp, HubSpot |
| Data syncing | The same record kept consistent across a store, a sheet and a CRM, without copy and paste | Google Sheets, Airtable, Shopify, WooCommerce |
| Social media posting | Posts, posters and short videos generated from one brief and scheduled | Meta, Google Drive, video rendering APIs |
| AI call and voice agents | A phone line that answers, qualifies and books, or grades every recorded call | Vapi, Retell AI, ElevenLabs, Twilio |
| AI messaging and chatbots | An assistant on your website or WhatsApp that answers from your own content and captures the lead | WhatsApp, your website, your CRM |
Which tools does Foundreco build with?
These are the platforms, models and systems Foundreco builds on and connects. If your business already runs on one of them, the automation is built there, rather than moving you onto something new.
Platforms and code
AI models, frameworks and voice
Systems it connects to
Also built with and connected to, where there is no logo to show:
n8n, Zapier, Make or GoHighLevel: which should you use?
The right platform depends on volume, how much logic the workflow carries, and what your team already pays for. The short version:
| Platform | Best when | Watch for |
|---|---|---|
| n8n | High volume, branching logic, custom code steps, or you want to self-host | Someone has to own the server if you self-host |
| Zapier | Simple, low-volume flows between popular apps, set up fast | Cost grows with every step that runs |
| Make | Visual, multi-branch scenarios with a lot of data mapping | Complex scenarios get hard to read without discipline |
| GoHighLevel | Your CRM, calendar, SMS and email already live there | Workflows multiply and start to conflict unless they are structured |
| Custom code | The logic is the product, or no platform handles it | You now maintain software, not a workflow |
The pricing models are the part most people miss. Zapier counts a task each time it successfully completes a unit of work, so a five-step Zap costs more per run than a two-step one. n8n Cloud bills per workflow execution, however many steps the workflow has, and the self-hosted Community Edition is free. For a workflow that runs thousands of times a month, that difference decides the platform. The n8n automation page covers when self-hosting is worth it.
What can an AI call agent or voice agent do?
An AI call agent answers or places phone calls in a natural voice, follows a script with room for real conversation, and writes the outcome back to your systems. A voice agent does the same on your website or in your app. Foundreco builds them on Vapi and Retell AI, with ElevenLabs voices and Twilio numbers.
One legal point before any outbound calling. In the United States, the FCC ruled in February 2024 that an AI-generated voice counts as an artificial voice under the TCPA, which means outbound calls with one need the recipient's prior express consent. Inbound agents answering people who called you are a different matter. Other countries have their own rules, and this is worth settling before the build, not after.
AI messaging and website chatbots
The same models can answer questions on your website or in WhatsApp, from your own content, and pass a qualified lead into your CRM with the conversation attached. That is its own page, because a chatbot that sounds confident and is wrong costs more than no chatbot: AI chatbot development covers how they are built, where they run and what they cost to operate.
Automation projects Foundreco has delivered
A sample of eight, each with the price range, duration and industry as recorded when it was delivered. Client names are withheld.
AI music radio automation in n8n
An online music radio that ran itself. On a schedule the workflow collects the latest music news, has GPT-4 write a radio script, turns it into natural voice audio with ElevenLabs, lays background music under it with FFmpeg, logs everything to Google Sheets, and sends the finished segment and playlist update to the radio platform through its API. A second workflow picks eligible videos by length, avoids repeats and updates the playlist.
- Schedule trigger
- Get latest music news
- AI scriptGPT-4
- Create radio content
- Text to speechElevenLabs
- Add background musicFFmpeg
- SaveGoogle Sheets
- If
- Edit playlist
- Call APIradio platform
More detail on the n8n automation page.
Browser order automation in n8n
Built to take order processing out of manual work. The workflow checks for new WooCommerce orders, removes duplicates, loops through each one against set conditions, prepares the customer details, then runs a browser automation that places the order. It checks whether the order was created and updates the WooCommerce status to match.
- Schedule trigger
- Get ordersWooCommerce
- Remove duplicates
- Loop over items
- If
- Map customer data
- Run browser automation
- Parse result
- Order created?
- Update order statusWooCommerce
AI email support and FAQ replies in n8n
Built to take repetitive questions out of a support inbox. Each new Gmail message is extracted and its intent classified by AI, then matched against a knowledge base using embeddings. The relevant answers become context for the response model, and a confidence check decides what happens next: a confident answer is sent and logged, an uncertain one goes to a review queue and the support team is told in Slack. Each week the logs are summarised and sent by email and Slack.
- New emailGmail
- Extract content
- Classify intent
- Search knowledge baseembeddings
- Build context
- Generate response
- Confidence check
- Auto-reply and log
- Or: review queueSlack alert
This is the same pattern a website chatbot should follow, covered on AI chatbot development.
Shipping and fulfilment automation in n8n
Built so shipping starts the moment an order is paid, with no manual steps. A paid WooCommerce order starts the workflow: it extracts the order, validates the address, calculates weight and dimensions, fetches rates from Shippo, picks the carrier and generates the label. The order is updated in the store, the label PDF is saved to Google Drive, and the team and the customer are both emailed. A bad address or a failed label raises an alert straight away instead of a silent gap.
- Order paidWooCommerce
- Extract order
- Validate addressShippo
- Weight and size
- Get rates
- Select carrier
- Generate label
- Update order
- Save labelGoogle Drive
- Email team and customerGmail
AI real estate launch campaigns from one form, in n8n
A developer launching several property projects was rebuilding the same marketing from scratch each time. One intake form now starts everything: a Google Drive folder tree and a tracker row with a project ID, then a single Gemini call that returns a bilingual content library as structured JSON (website copy, ad headlines, a five-step email sequence, WhatsApp and SMS messages). Separate workflows build the HubSpot landing page, the posters and the video reels, and an outreach list comes from Apollo. A Meta ads workflow is part of the system and was switched off in the build shown.
- Intake form
- Build prompt
- Generate contentGemini
- Parse response
- Upload filesGoogle Drive
- Update statusGoogle Sheets
- Landing pageHubSpot
- Posters and reelsJSON2Video
- Email: content readyGmail
GoHighLevel CRM and booking automation for a dental clinic
The goal was fewer missed appointments and less manual follow-up. The pipeline has a stage for every appointment state, and a workflow for each one sends the right SMS or email when a booking moves: reminders, rescheduling, missed-appointment follow-up and post-visit messages, with the calendar connected so bookings and notifications stay in step.
- Confirmed
- Rescheduled
- Cancelled
- No show
- Completed
GoHighLevel lead follow-up restructure for real estate
An existing GoHighLevel and REIReply setup needed cleaner routing, reply handling and protection against workflows conflicting with each other. After a review of the client's SOP, the follow-up was rebuilt as tiered sequences with tag-based routing: each step waits a set number of days, and a reply takes the lead out of the sequence while silence moves it to the next pipeline tier. Lead types branch on tags, so each gets its own messages.
- Branch on tag
- Day 7 message
- Wait
- Reply: tag and exit
- Timeout: next tier
Multi-tenant AI call quality assurance platform
Built for a QA consultancy whose clients could only review a small sample of their calls by hand. The platform transcribes every recording with OpenAI Whisper, grades it against the client's own scorecard with GPT-4o, and puts a verbatim quote behind every score, then routes the calls that matter to a human reviewer who can override any grade. Each client is an isolated tenant, enforced by row-level security in Supabase, and audio is decoded in the browser before upload. Built on Next.js 15, TypeScript, PostgreSQL, Deno Edge Functions, pg_cron and Square.
How an automation project runs
- A free audit. You describe the task your team repeats most. You get back what is worth automating, what is not, and which platform fits.
- A fixed quote. One price and a delivery date before anything is built. Changes are quoted before they happen.
- Built in your accounts. By default the workflow lives in your own n8n, Zapier, Make or GoHighLevel account, so it keeps running if we stop working together.
- Tested with real data. Edge cases first: duplicates, missing fields, replies that arrive at the wrong moment.
- Handed over. A plain-English note of what each workflow does and what to check if it stops.
When automation is the wrong answer
If the process changes every week, automate it later. If it happens five times a month, a checklist is cheaper. If nobody can say what "done" looks like, a workflow will only do the wrong thing faster. The audit exists partly to say so, and it will.
Questions about AI automation
How much does an AI automation project cost?
How long does an automation take to build?
Should I use n8n or Zapier?
Do I own the automations?
Can you restructure automations that already exist?
Is it legal to use an AI voice for outbound calls?
Tell me the task your team repeats most
One paragraph is enough. You get back what is worth automating, which platform fits, and a fixed price, including "this is not worth automating yet" when that is the truth.