We build the agents and workflows that take the repeatable work off your team: support triage, order operations, lead follow-up, reporting. Working software in weeks, not a roadmap deck.
#4821 · 09:14
Where is my order?
Order 77-1094 · shipped Tuesday
#4822 · 09:16
The mug arrived cracked
Order 77-1101 · photo attached
#4823 · 09:18
Change the delivery address
Order 77-1088 · not shipped
#4824 · 09:21
Invoice for PO-118?
Finance · repeat sender
#4825 · 09:23
Can I get it before Friday?
Order 77-1107 · checkout open
A real inbox mix: four requests, three actions, one handover. The escalation is the feature.
An AI automation agency builds and runs the software that does a company's repeatable work: reading requests, deciding what they need, and taking the action inside the tools you already pay for.
The rest of this page is the long version of that sentence.
The difference from a classic automation shop is judgement. Instead of if-this-then-that, the system can take the same request written five different ways and still put it in the right queue, with a log of why it did.
Most of the work we do sits in four places: the support inbox, order operations, finance admin, and reporting. If your team screenshots a spreadsheet into Slack every Friday, that is our kind of job. If the process only exists in one person's head, we usually spend the first two weeks writing it down before automating anything.
We are not an AI research lab and we do not train models. We connect models that already work to the systems that already hold your data, then put guardrails around the result so it can be trusted on a Tuesday afternoon when nobody is watching.
Six ways clients start. Most pick one, prove it in a quarter, then add the next. Every engagement is fixed scope with the hours named up front.
An agent wired to your docs, order system, and CRM.
It reads the request, looks up the record, and answers or acts. Support triage, research, lead qualification, scheduling, and the internal questions that currently interrupt someone senior.
First project: tier-one inbox triage, four weeks
The forty-step manual process, rebuilt as one flow.
Intake, validation, decisions, updates, and notifications, running on events instead of reminders. Built in n8n, Make, or Python once the logic outgrows a visual builder.
First project: refunds and replacements, with policy checks
Chat and voice that can check a calendar, not just apologise.
Retrieval over your real content, function calling for the parts that need a system, and a clean handover to a human with the transcript attached.
First project: booking assistant that holds the slot
Lead in, score, route, follow up, book.
Ad platforms, CRM, email, and calendar joined into one funnel. The follow-up goes out in minutes, stops the moment a person replies, and reports on pipeline rather than form fills.
First project: five-minute lead response
One source of truth for the numbers.
Extract, transform, load, plus the warehouse model underneath. No stale spreadsheets, no duplicate records, and no weekly argument about whose dashboard is right.
First project: Monday revenue report, assembled at 6am
Guardrails that hold when the model is unsure.
Confidence thresholds, prompt-injection defence, access control, audit logs, and human approval before anything irreversible happens. This part is not optional and it is not an upsell.
First project: approval gate before anything sends
Where this lands most often
SaaS & technology
Onboarding, churn signals, support deflection, and product-led growth loops.
E-commerce & D2C
Inventory alerts, order operations, review collection, and returns.
Professional services
Intake, proposal drafts, scheduling, and client reporting.
Financial services
Document processing, compliance checks, KYC, and risk scoring.
Healthcare & clinics
Appointments, patient intake, follow-ups, and insurance checks.
Marketing agencies
Content pipelines, client dashboards, and media-buying signals.
We are not loyal to a stack. We are loyal to whatever your team can maintain after we leave.
OpenAI
Anthropic
Gemini
n8n
Make
Zapier
LangChain
Pinecone
Supabase
PostgreSQL
AWS
Azure
HubSpot
Salesforce
Slack
NotionAutomation fails as a design problem long before it fails as a technology problem. These are the four things we fix before a model goes anywhere near a customer.
A prototype that answers three scripted questions is easy. Nobody mapped what happens on the fourth, when the model is wrong and a customer is waiting.
The knowledge base is two years stale, duplicated between Notion and Drive, and contradicts the policy PDF. Retrieval returns confident nonsense.
Automation needs an exit. Without a threshold and a queue, the system either guesses on hard cases or blocks the process entirely.
Models change, sites change, someone renames a field. Without logs and a weekly review, a workflow degrades quietly for months.
The audit comes first and it is allowed to end in a no. If the numbers do not support automating the process, you keep the document and we part on good terms.
We shadow the team and log the tasks that repeat, how long they take, and what they cost. You get a ranked list with hours attached, including the ones we would not automate.
Tools, model, memory, and the thresholds between automatic and human. Written down before anyone builds, so you can argue with the design while it is still cheap to change.
Shipped weekly into a staging workspace and tested against real tickets from last month. You see it fail on the awkward cases before your customers do.
Sixty days of log review, threshold tuning, and handover documentation. Then either we keep running it, or your team takes the repo and the runbook.
Most business automation agencies sell hours. We sell a fixed-scope build, and the difference shows up in the third column of every contract.
Swipe the table to see the other two columns.
| AAA Digital | Typical agency | In-house hire | |
|---|---|---|---|
| First workflow live | 3 to 6 weeks | 8 to 14 weeks | 3 to 5 months |
| Who owns the code | You, from day one | Licensed to you | You |
| How you pay | Fixed scope per build | Monthly retainer, hours unclear | Salary, benefits, tooling |
| When it breaks at 2am | We are on call for 60 days | Ticket queue | The one person who built it |
| After handover | Runbook and docs, or stay on | Handover is a new project | Knowledge walks out eventually |
Move the three sliders to your numbers. This is the same arithmetic we run in the audit, before anyone quotes a build.
Support triage usually lands near 60. Anything involving judgement or money over a set limit, keep lower.
Guessing high is the fastest way to lose the argument later. If the model only works when you assume forty hours a week, it does not work.
Your estimate
A model, not a quote. It ignores the cost of review time and the workflows that turn out not to be worth building, which is exactly why the audit exists.
A support agent that resolved 62% of tier-one tickets without a person. First response went from four hours to under two minutes, and engineering-support time dropped by forty hours a week.
Abandoned-cart and post-purchase flows built on purchase behaviour and send-time prediction. Revenue per email up 127%, with the same list and no extra sends.
Proposal generation, contract routing, and onboarding scheduling automated end to end. Time from qualified lead to signed contract fell from eleven days to three.
If you have a queue, a spreadsheet, or a person who answers the same question all day, that is enough to start. We will map it and tell you what it is worth.
Ranges, because scope decides the number. Every proposal lists the workflows, the hours, and the success measure before anything starts.
Not included: your existing software licences, ad spend, and model API usage, which usually runs $20 to $200 a month at this scale. We tell you the real figure once we know the volume.
| Engagement | Typical |
|---|---|
| AI workflow auditone-time, credited against a build | $2,500 – $5,000 |
| Single workflow buildone-time, fixed scope | $5,000 – $15,000 |
| AI agent developmentone-time, integrations included | $15,000 – $50,000 |
| Automation retainerper month, several live workflows | $8,000 – $25,000 |
The audit fee is credited against the build if you go ahead.
If your question is not here, ask it on the call. We would rather answer it before you sign anything.
Still deciding?
Send the workflow you are stuck on. You will get a straight answer on whether software should own it, even if the answer is no.
An AI automation agency builds software that does a company's repeatable work: reading requests, deciding what they need, and taking the action inside the tools you already use. The difference from older automation is judgement. The system can handle the same request written five different ways and still send it to the right place, with a log of why. We design it, build it, and stay on to watch it run.
Written by Aayush Bucha, founder
Reviewed 28 October 2026 · we update this page when the numbers change
One workflow, four weeks
Thirty minutes, no deck. We will ask what happens today, what it costs in hours, and whether software should be doing it at all. If the answer is no, you have a useful document and we have not wasted your morning.
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