Services
AI Automation Services for Small Businesses
Akif Wani builds practical AI automations for small businesses and agencies — customer-facing chatbots, document and email processing, lead qualification, and multi-step workflow agents — using the Claude API, n8n, and Make.com. The work targets repetitive processes that consume staff hours weekly. Automations are scoped against a specific process you can measure, not deployed as a general-purpose assistant.
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What's included
Process audit before anything is built
Which of your processes are actually worth automating, and which are not. Some tasks look automatable but have too many exceptions to be worth it — you will be told that before money is spent rather than after.
Workflow automation
Multi-step workflows in n8n or Make.com connecting the tools you already use — form submissions into your CRM, enquiries routed and tagged, data synchronised between systems, scheduled reports assembled and sent.
AI-powered document and text processing
Claude API integrations that read and act on unstructured input — extracting fields from invoices and forms, summarising long documents, classifying and routing inbound email, and drafting responses for human review.
Customer-facing chatbots
Chatbots grounded in your actual documentation and product information rather than answering from general knowledge, with clear handoff to a human when the question exceeds what they should answer.
Lead qualification and routing
Inbound enquiries assessed against your criteria, enriched, prioritised, and routed to the right person, so the sales team spends its time on leads worth their time.
Website integration
Automations wired into the site itself — form handling, quote generation, booking flows, and content workflows connected to your existing WordPress, WooCommerce, Shopify, or Next.js build.
Who this is for
- Small businesses losing staff hours weekly to repetitive manual processes
- Agencies wanting to automate reporting, onboarding, or client communication
- E-commerce operations handling high volumes of repetitive customer enquiries
- Teams drowning in inbound email or form submissions that need triage
- Businesses that want AI applied to a specific measurable process, not as a buzzword
When this isn't the right fit
This is not the right fit if you want AI deployed because it is fashionable but cannot name the process it would replace. It is also not right for processes with high exception rates and serious consequences for error — some work should stay with a human, and you will get that answer rather than a build you regret.
Process & timeline
- Step 1
Process audit
2–4 daysA walkthrough of the process you want automated: what triggers it, what decisions it involves, how often exceptions occur, and how much time it currently costs. This determines whether automation is worth it at all.
- Step 2
Solution design
2–5 daysThe proposed automation mapped out step by step — the tools involved, where AI is used versus deterministic logic, and where a human stays in the loop. Reviewed and agreed before build.
- Step 3
Build
1–3 weeks depending on complexityWorkflow construction, API integration, prompt engineering and testing, and error handling for when an upstream service fails or returns something unexpected.
- Step 4
Testing against real data
3–7 daysThe automation is run against real historical cases, including the awkward ones, so its failure modes are known before it touches live work.
- Step 5
Deployment and monitoring
1–2 daysLive deployment with logging and alerting, so a silent failure is visible rather than discovered weeks later.
- Step 6
Handover and iteration
Ongoing by arrangementDocumentation of how the automation works and how to adjust it, plus a review period to tune behaviour against real usage.
Tools & pricing
Tech stack
- Claude API
- n8n
- Make.com
- Node.js
- TypeScript
- Webhooks
- REST APIs
- Supabase
- WordPress and WooCommerce integration
Process audit
Quoted per engagement
An assessment of which processes are worth automating and what the realistic return is, delivered as a written recommendation.
Single workflow automation
Quoted per project
One defined automation — lead routing, document processing, or a reporting workflow — built, tested, and deployed.
Chatbot or AI assistant
Quoted per project
A chatbot grounded in your documentation, with human handoff, integrated into your existing site.
AI automation is quoted per project rather than from a starting price, because the same-sounding request can be a two-day job or a three-week one depending on how many exceptions your process carries. Ongoing API costs for the Claude API and any automation platform are billed by those providers directly and are separate from the build quote.
AI Automation
AI Automation FAQs
What kind of business processes can AI automation actually handle?
AI automation works well on repetitive processes with consistent inputs: routing and tagging inbound email, extracting fields from invoices and forms, qualifying leads against set criteria, summarising documents, generating routine reports, and answering common customer questions from your documentation. It works poorly on processes with high exception rates or where an error carries serious consequences.
How much does AI automation cost to build?
AI automation is quoted per project after a process audit, because the same request can be a two-day build or a three-week one depending on how many exceptions the process carries. Ongoing usage costs for the Claude API and platforms like n8n or Make.com are billed by those providers directly and sit outside the build quote.
Do I need to replace my existing tools to use automation?
No. Automations are built to connect the tools you already run rather than replace them. n8n and Make.com integrate with hundreds of common business applications, and anything with a documented API can be connected directly. Replacing working software is usually the most expensive and disruptive way to solve an automation problem.
What is the difference between a chatbot and a workflow automation?
A chatbot is customer-facing and conversational — it answers questions in real time and hands off to a human when it should. A workflow automation runs in the background without conversation, triggered by an event such as a form submission, then processes and routes it. Many businesses need the workflow automation far more than the chatbot.
Will an AI chatbot make things up about my business?
That risk is why chatbots here are grounded in your actual documentation and product information rather than answering from general knowledge, and are given an explicit handoff path when a question exceeds what they should answer. A chatbot allowed to answer anything will eventually answer something wrong — constraining scope is the fix.
Which AI model do you build on?
The Claude API is the usual choice for text processing, document extraction, and chatbot work, integrated through n8n, Make.com, or directly in Node.js and TypeScript. Model choice is made per project against what the task actually needs, since the most capable model is not always the right cost or latency fit for a high-volume workflow.
How do I know the automation is working?
Every automation ships with logging and alerting, so a silent failure surfaces immediately rather than being discovered weeks later when work has quietly stopped happening. Before going live, the automation is run against real historical cases including the awkward ones, so its failure modes are known rather than discovered in production.
Need ai automation?
Describe what you need and you will get a fixed written quote covering price, timeline, and deliverables. Scoping usually takes 24–48 hours.
Or email info@akifwani.com