AI automation services that take the busywork off your team.

What AI automation services cover, and who they are for

AI automation services take the work your team repeats every week and run it automatically inside the tools you already pay for. That means answering the same customer questions, typing orders into a sheet and chasing unpaid invoices, while a person stays in charge of what reaches your customers. I am an AI automation specialist, and I build these systems for small businesses, nonprofits and founders, mostly in the US.

In practice that covers customer messages, sales follow-up, invoices and accounting, reading documents, reports, bookings, staff admin and content, plus AI agents for jobs with many steps. Most of it is plain workflow automation, sometimes called business process automation: when this happens, do that, in this order. AI goes in only where a step needs judgement, such as reading an invoice that arrives as a photo. Everywhere else, a plain rule costs less and cannot invent facts.

This suits you if a few people spend part of every week copying, retyping or chasing. It suits a shop whose customers message at night, a nonprofit with one coordinator and a spreadsheet, and a founder who still does the admin personally. It does not suit a process nobody can describe yet; writing it down comes first, and I will say so.

I also work with businesses in Nepal; if that is you, the page on AI automation in Nepal covers local examples and quotes in NPR. If you are not sure what to automate, a free automation map comes first: I list every task your team repeats and rank them by the hours they eat.

The full list of AI automation services I build

Nobody needs all of this. Most businesses start with one or two items.

WhatsApp automation

The WhatsApp Business API and automatic replies. The free WhatsApp Business app is fine until messages arrive faster than one phone can answer. I move you to the WhatsApp Business API and set up replies for the daily questions: prices, hours, location, delivery areas. You approve every answer first, and anything else goes to a person.

Order capture. A customer writes “two dozen cupcakes, Saturday at 3”, or sends a photo of a handwritten list. The workflow pulls out the items and date, adds a row to your Google Sheet or order system, and asks the customer to confirm. Unclear messages, handwriting most of all, wait for a staff member.

Catalog, order and delivery updates. WhatsApp can hold your product catalog in the chat, so customers browse and order in one place. Status messages (confirmed, packed, out for delivery) then go out from your Shopify, WooCommerce or sheet data, saving the “where is my order?” calls.

Appointment reminders and opt-in broadcasts. Reminders go out before each visit with a button to confirm or reschedule. Offers go only to people who opted in, using templates that Meta approves first. Meta bills for most template messages, so I agree the volume with you before any broadcast.

A shared team inbox, and handoff to a person. Several people can answer one WhatsApp number from a shared inbox such as Chatwoot, with chats assigned and tagged. The bot takes the first reply and, when a customer asks for a human, hands the chat over with the history attached.

Viber, Messenger, Instagram, SMS, email and Telegram

Viber automation. Viber is popular in parts of Eastern Europe, the Middle East and South Asia, so some businesses need it beside WhatsApp. I build the same flows there: answers, order capture, reminders and a handoff to staff.

Facebook Messenger and Instagram DM automation. People ask the same few things in DMs and comments: price, availability, where to buy. The bot answers those, tags the chat as a lead, an order or a support issue, and logs it in your CRM. Complaints go to a person.

SMS and email notifications. Order confirmations, receipts, reminders and payment-due notices go out on their own when the event happens in your system. That is email automation at its plainest. Email goes out from your own account and texts from a provider such as Twilio, in wording you approved.

Telegram bots. My Daraz price-tracker bot is live on Telegram. At Appynox, the AI-first agency I co-founded, we built the Linkify Social bot, which replies with the link to the product shown in a social post. For a business, the same pattern covers order look-ups and stock alerts.

AI chatbots and AI customer support

A website chatbot built on your own documents. AI chatbot development mostly comes down to what the bot may know. I give it your policies, price lists and FAQs to read at each answer, so every reply traces back to one of your pages and the bot says “I do not know” when none fits. It works in English and Nepali, and fixing a wrong answer means editing a document.

Support triage and FAQ answers, with handoff. The bot reads each ticket, sorts it by type and urgency, and tags it in Zendesk, Help Scout or a shared inbox. Routine questions get an answer or a draft. Refunds, complaints and anything emotional go to a person with a short summary. AI customer support works best as a fast first reader.

AI voice agents for calls and missed-call follow-up. A voice agent can answer the phone, take a name and the reason for calling, book a slot and send the details to your calendar or CRM. A lighter version texts a booking link after a missed call. Voice is where I am most careful: I can build these, and I test them on real calls before an agent talks to a customer. Anything it cannot handle goes to a person.

Lead generation, follow-up and CRM automation

Lead capture into your CRM. Web forms, WhatsApp messages, Instagram DMs, booking pages and the info@ inbox all write one record, with its source, to HubSpot, Zoho, Pipedrive, Airtable or a Google Sheet. Your team decides which leads get a call.

Enrichment and scoring. Each new lead gets a lookup of public details, such as company site, size and industry, and a score against rules you set, like “inside our service area”. You can see why a lead got its score and override it.

Personalised first messages. A mail merge only slots a name into a template. These messages mention something real about the person’s business, found on their site, and are written in your tone. You approve the drafts, then whole batches once you trust them.

Follow-ups that stop on reply, and reply sorting. The second and third message go out on schedule and stop the moment the person answers, by email, WhatsApp or anywhere the workflow can see. Replies are then sorted into yes, not now, wrong person, out of office, question and unsubscribe. “Not now” gets a reminder, unsubscribes are removed, and your people spend their time on the live ones.

A weekly call shortlist. Each week you get a list of who is worth phoning: warm replies, quotes about to expire, leads that went quiet after showing strong interest. The calls stay yours.

CRM hygiene. CRM automation also keeps the data clean, because CRMs go stale: duplicate contacts, empty fields, deals stuck in the wrong stage for months. The workflow merges obvious duplicates and flags stale deals for the owner. It never deletes a record without a person confirming.

Orders, invoices and accounting

Order intake. Orders arrive by email, form, chat and phone note. The workflow gathers them into one list, checks items and prices against your catalog, and creates the order or a draft invoice. Odd items or missing details go to a person first.

Invoice automation and payment reminders. The workflow creates the invoice from the order or accepted quote, sends it and tracks it until paid. Overdue ones get a polite reminder, a firmer one later, and a note to you when a customer needs a call. You set the tone and can pause any customer.

Accounting sync. Sales, payments and expenses flow into QuickBooks, Xero, Tally or an Excel workbook without retyping. Your bookkeeper sees categorised entries plus a short list the workflow was unsure about, which a person confirms.

Supplier price lists and purchase orders. Suppliers send prices as PDFs, spreadsheets and emails, each laid out differently. The workflow reads them into one comparison sheet, flags what changed and drafts purchase orders when stock runs low. A person approves each order.

Inventory and reorder alerts. Stock counts from your sales system are checked against your reorder levels. When an item drops below its level, the right person gets the count and the usual supplier, with a draft order if you want one.

E-commerce order sync. Orders from Shopify, WooCommerce and Daraz (for sellers in South Asia) land in one place with stock levels. A sale on one channel updates the others, and odd orders are flagged for a person.

Document processing and data entry automation

Invoice and receipt extraction. Document processing often starts here. A photo of a receipt or a supplier’s PDF invoice is read for vendor, date, line items and total, then written to your accounting software or a sheet. Uncertain values are highlighted beside the original for a person to check.

Forms and PDFs into structured data. Intake forms, applications, signed agreements and scanned paperwork become rows with proper fields instead of files in a folder. A language model reads the messy ones, plain rules read the tidy ones, and a person reviews the exceptions.

Long documents, summarised. Contracts, grant applications, reports, call recordings and long email threads become a one-page summary of dates, amounts, obligations and open questions, each pointing to its source page. I would not use this in place of a lawyer reading a contract.

Data entry automation between systems. If a person reads a value on one screen and types it into another, it can usually be automated: new customers from a booking tool into the CRM, finished jobs into invoicing. When a tool has no API, I look for a scheduled export or an import file first.

Spreadsheet clean-up. Inherited sheets collect names in several formats, dates typed as text and duplicate rows. I write a repeatable clean-up (Google Apps Script, formulas or a short Python script) that logs every change and leaves your original untouched.

Web scraping and price or competitor monitoring. The workflow checks public pages on a schedule, such as competitor prices, stock status or a grant portal, and reports changes with the old value, the new value and the link. Scraping stays on public pages, within each site’s terms.

Reporting automation, dashboards and alerts

Daily and weekly reports that build themselves. Reporting automation pulls figures from where they already live (sales, ad spend, tickets, bookings), arranges them in the format you already use and sends them to the people who read them. Whoever built the Friday report gets that time back, and someone skims the summary before it goes out.

Dashboards and KPI alerts. One dashboard in Looker Studio or Google Sheets shows the numbers you check daily, so nobody asks “where are we this month?” in a chat. Alerts watch the measures you choose, such as refunds, response times or stock-outs, and message you when one crosses a limit you set.

Appointment booking automation

Appointment booking and reminders. Customers pick a slot on Cal.com, Calendly or a Google Calendar page, and the workflow sends the confirmation, intake questions, calendar invite, reminders and a reschedule link. The booking lands in your CRM with the answers attached, and you control which services can be booked online.

No-show follow-ups. After a missed appointment, a polite message offers a new slot and the miss is logged, so you can see patterns by service, day or staff member. For repeat no-shows a person decides what to do, such as asking for a deposit.

Staff, hiring and internal knowledge

Staff rosters, attendance and leave. Availability, attendance, shift swaps and leave requests arrive through a form or a chat message and update one roster, so gaps show early. A manager approves leave and swaps, and the workflow never decides who gets a day off.

Onboarding checklists and SOPs. A new hire, client or job triggers the same checklist every time: accounts created, documents sent, first tasks assigned, each step with an owner and a due date. Writing the process down once also shows which steps nobody had written.

CV screening and interview scheduling. The workflow reads applications against criteria you set and returns a shortlist with a short reason for each name. Candidates then pick interview slots from the hiring manager’s calendar. A person sees every application and decides who is interviewed. Some US cities and states regulate automated hiring tools, so check the rules where you hire.

An internal assistant for staff questions. Staff ask in Slack, Teams or WhatsApp where the leave form is or how refunds work. The assistant answers from your SOPs, links the source and says so when it finds none. Those misses become a list of what your documentation lacks.

Meeting transcription and notes. The workflow transcribes calls and summarises them into decisions, action items with owners and dates, and open questions, then files them in your project tool or CRM. Participants are told the call is recorded, and attendees check the notes.

Content, translation and video

Social media automation. The system researches ideas, writes a caption for each platform, designs the graphics, checks the work and schedules it, with your approval on every post. It runs 10 brand accounts for a Philadelphia hospitality entrepreneur, and the AI social media automation page has the details.

Blog, newsletter and product-description drafting, with a human edit. Drafts come from your notes, calls, product data and past posts, follow your written voice rules and list their sources. Sizes and materials are taken from your sheet, never invented. A person edits and approves before anything is published, and each correction becomes a rule the next draft follows.

Nepali and English translation. Product pages, notices and messages are translated both ways using a glossary of your terms, so they stay consistent. A fluent reader checks anything customer-facing before it goes out.

Video at volume. At Appynox we built a production system that made 85 social videos for SameShot and 65 shorts for WideMath, with captions, motion text, sound, every platform size and automatic checks on each render before a person reviews it. The video at volume case study has the detail, and AI video editing covers client work.

AI agents and custom integrations

AI agents and multi-agent systems. An AI agent is a model given a job, some tools and rules about what it may do. A multi-agent system splits a bigger job among agents that each do one thing and check one another. My social media system uses 13 specialised sub-agents (research, writing, design, an independent reviewer that starts fresh, scheduling, analytics) and produced 160+ posts in its first five weeks, each approved by a person (case study).

Guardrails for agents. Every agent I build gets a short list of allowed actions, limits on sending and spending, and a log of every step. Anything that cannot be undone waits for a person.

Custom integrations. When no ready-made connector exists, I join systems through their APIs and webhooks, using Python, self-hosted n8n, Google Apps Script or Microsoft Power Automate. The aim is the simplest build that does the job and that someone else can maintain, with logging and alerts included.

AI automation for small businesses, by industry

AI automation for small businesses looks different in every trade. These are illustrations, not a client list.

• Restaurants and food businesses. Phone, website and delivery-app orders (DoorDash, Uber Eats) reach one screen, and supplier orders are drafted from low stock. The nightly sales report writes itself, and a manager approves every supplier order.
• Retail and e-commerce. Shopify or WooCommerce orders sync with stock, and shipping updates reach customers on WhatsApp or email. Support is sorted into order status, returns and the rest, and returns go to a person.
• Clinics and health practices. Reminders go out before appointments, and intake forms are read into the patient record for staff to confirm. The reminders carry only the time and place, never clinical detail.
• Real estate. Enquiries from Zillow, Instagram and your website enter the CRM in one format and get a first reply. Follow-ups continue until the person answers, and the agent gets a weekly call list.
• Professional services (law, accounting, consulting). Intake forms become client records, and documents are sorted and summarised. Files stay in your own systems, and a professional reads every summary before it informs advice.
• Agencies. Client reports build themselves from ad and analytics accounts, and status updates are drafted from the project tool. A senior person reviews anything a client will see.
• Nonprofits. Donor receipts go out when a gift arrives, volunteer shifts run from one form, and grant reports are assembled from data you already collect. Staff sign off on anything for a funder.
• Education and training. Enquiries and applications are sorted and answered, and class and fee reminders go out by message. An assistant answers student questions from the handbook.
• Travel and hospitality. Booking enquiries from email, Instagram and WhatsApp collect into one list with a drafted reply. Confirmations, pre-arrival messages and review requests go out on their own.
• Home services and trades. A missed call gets a text with a booking link, and quotes and invoices are built from job notes. The owner approves each quote before it leaves.

How a project works with an AI automation specialist

A project has four phases: watch, map, build one and run. You can stop after the second and owe nothing, because the map is free and yours to keep.

1. Watch. I spend time with the people doing the work and change nothing. I note what each person repeats, which tools they open and where work sits waiting.
2. Map. I send you a written map: each repeating task, what it costs you in hours each week, how hard it is to automate, and the order I would tackle them in.
3. Build one. You choose an item from the top of the map and I build it against your real work, not a demo. I would rather ship one automation that runs than hand you a long plan.
4. Run. Then it runs. It keeps a record of what it does and warns you when something breaks, and you add the next item at your own pace.

While I watch, I look at four things:

• People. I ask what each person does in a day, in their own words, including the parts nobody mentions.
• Software. I list every tool in use, including the spreadsheet nobody admits to and the WhatsApp group doing half the job.
• Handoffs. I look for places where work waits for one person, gets retyped from one system into another, or falls between two people who each thought the other had it.
• Documentation. I check what is written down, what is out of date, and what exists only in one person’s head. The last of these costs the most.

The tools I use, and why they are boring on purpose

I choose between n8n, Make and Zapier by the shape of the work. Make and Zapier automation suits lighter flows and teams who want to edit things themselves, and both charge by how much your workflows run. For high volume I self-host n8n, and n8n automation then costs you a small server instead of a fee for every task.

Your data stays where it is: Google Workspace, Microsoft 365, Excel and your accounting system. Messages travel through WhatsApp, Viber, Messenger, Instagram and plain email, where your customers already are.

A language model goes in only where a step needs judgement. It costs money on every call and can be confidently wrong, so plain rules or a few lines of code handle every other step.

I pick proven tools on purpose. They are documented, other people can maintain them, and other users have already found most of their failures. If a ready-made product already does the job, I will tell you to use that, and there is nothing for me to build.

The rules I work under: you keep the keys

I state these before you ask, and they cover every build.

1. Nothing goes out without a person’s yes. Posts, outreach emails and quotes wait in a queue until someone approves them. Routine answers, like opening hours, work because you approved the wording and sources first, and anything outside them goes to a person. Anything you cannot pause is a risk, so every automation I build has an off switch.
2. Your accounts stay yours. Everything runs inside tools you own and pay for. You can read the log of every action, and one click removes my access.
3. Your staff stop retyping, not working. I aim at the copying and pasting. If your goal is fewer people, I am the wrong person to call.
4. It fails loudly. Each automation keeps a log and sends an alert when a step fails, so the problem reaches you before it reaches a customer.
5. You get the handover. You receive the documentation, the access details and a plain written explanation of how each part works, so another person can take it over.

What AI automation costs, and what drives it

I do not publish a price list, because two jobs that sound alike can differ a lot in size. These things move the cost:

• Steps. A workflow with a few steps and no exceptions is small. Many steps and a long list of special cases take more design and testing.
• Systems. Each system I connect (CRM, accounting, WhatsApp, calendar) has its own login, limits and quirks, and each one adds work.
• Volume. A handful of messages a day and a constant stream need different designs, and the stream costs more to run.
• Per-message fees. Meta bills for most WhatsApp Business API template messages, at rates that depend on the message type and the customer’s country and that change now and then, so I check the current table before quoting. SMS providers bill per text, and a provider that hosts your WhatsApp connection may add its own fee.
• Model usage. A language model bills by what it reads and writes, so long documents and busy channels cost more. A plain rule costs nothing per use.
• Upkeep. Tools change their APIs, passwords expire and customers write things nobody predicted. Someone has to read the logs and fix what breaks, and that can be me or a person on your team working from the handover.

That is why I start with one workflow: you see what it costs to build and to run before you commit to more. A written quote follows for each item you pick from the free map.

How to choose what to automate first

Begin with the task that eats the most hours and is safest to get wrong. A few questions sort the candidates:

• Does it repeat? Something that happens every day or week pays back. A task done twice a year usually does not.
• Can you write the rule down? If two staff members would handle the same case differently, settle that first.
• What happens when it goes wrong? A wrong reminder is cheap and a wrong refund is not, so start where a person can catch mistakes.
• Is the data reachable? It has to sit in a tool with an API, an export or an inbox I can read.
• Will someone own it? Each automation needs a person who reads its log and answers when it asks a question.

Leave alone anything that depends on a relationship or on judgement you have not defined yet, such as a condolence note or a dispute with a long-standing client. Automate around those with drafts and reminders. My longer checklist is in what to automate first in a small business.

How to start

The free automation map is the first step. On one call you describe an ordinary week, who does what and where work gets stuck, and I send you the written map afterwards. It is yours to keep whether or not you hire me.

You can book a 30-minute call, and the booking page shows your own time zone. If you would rather write first, send a short brief through the contact page.