Frictionless
AI Automation.
We automate the work your team should not be doing by hand. Your systems get connected, AI handles the judgement calls in between, and the repetitive part goes to agents that finish the task on their own. You keep full control over every step.
Last reviewed
What is AI automation?
AI automation is the use of artificial intelligence to run a business process end to end, including the steps that need judgement. Classic automation moves data between systems by fixed rules. The AI layer adds understanding, so the process can read an email, weigh an exception and decide what to do next without a person in the middle.
Why rule based automation keeps breaking.
| Aspect | Legacy automation | ATBM AI engine |
|---|---|---|
| Logic | Rigid if this then that, written for one exact case | Semantic understanding, so the process copes with wording it has not seen |
| Input | Breaks on anything unstructured | Reads text, voice and images the way a person would |
| Failure | Stops and waits for somebody to notice | Retries, corrects itself, escalates only what it genuinely cannot solve |
| Maintenance | Every API change means a rebuild | Built to absorb change, monitored so breakage surfaces before you feel it |
Three levels of AI automation.
Most companies do not need the top level on day one. They need the bottom one to actually work first. We build in this order for that reason.
- 01
Connected flows
Moving data without a human in the middle.
The foundation. Your CRM, inbox, calendar, forms and spreadsheets stop being separate islands. A lead that arrives in one system appears in every other one, correctly formatted, without anyone retyping it. This is the layer that removes copy and paste work, and it usually pays for itself first.
- Form submission creates a CRM record and a calendar hold
- Invoice data flows from the shop into accounting
- New client triggers folder, contract and onboarding sequence
- 02
AI in the loop
Judgement calls a rigid rule cannot make.
The layer where automation stops being a script. An AI step reads an incoming enquiry and decides whether it is a real lead or a supplier pitch. It summarises an hour of call recording into five lines. It drafts a follow up that references what the client actually said. Rules cannot do this, because the input is language, not a field.
- Inbound enquiries scored and routed by fit, not by keyword
- Meeting recordings turned into notes and next steps
- Personalised follow up drafted from the call transcript
- 03
Autonomous agents
A process that finishes without you.
The top layer. An agent is given an outcome rather than a set of steps, and it chooses how to get there. It looks things up, calls other systems, handles the exception it was not explicitly told about, and reports back when the outcome is reached. This is where automation stops being a time saver and becomes capacity you did not have before.
- Research a lead, qualify it, book the meeting, update the CRM
- Chase an unpaid invoice through the right escalation path
- Reconcile two systems that disagree and flag what it cannot fix
What we build on.
n8n
Our default orchestration layer. Self hostable, which matters when the data cannot leave your infrastructure. ATBM holds a verified n8n Level 2 certification.
Make.com
Used where a visual builder and a large connector library beat custom work. ATBM holds the Make Advanced and Make AI Automation certifications.
Agentic AI runtimes
OpenClaw and Hermes for agents that run as a permanent service rather than firing once per trigger. Both are self hosted and keep memory between sessions, which is what separates an agent that learns your process from a script that repeats it. This is the layer behind the third level above.
Custom services
Python and Node where no off the shelf connector exists, or where the volume makes a hosted tool the wrong economics.
ROI is our metric.
Efficiency is not an end in itself. It serves the margin. We map your processes and show you exactly how many hours come back to your team every month, before you commit to a build.
Request a process auditQuestions before you start.
What if our software has no API?
It is usually still automatable. Where no API exists we work with database access, scheduled file exports, email parsing or, as a last resort, a browser agent that operates the interface the way a person would. We check this in the audit and tell you upfront if a system is genuinely a dead end.
How is this different from Zapier or a normal workflow tool?
A rule based tool does exactly what you specified and stops the moment reality differs. What we build handles the cases you did not specify, because it reads meaning instead of matching fields. In practice that is the difference between a workflow that breaks every time a supplier changes an invoice layout and one that simply carries on.
Which tools do you build on?
n8n by default, because it can be self hosted and your data never has to leave your infrastructure. Make where its connector library saves real time. OpenClaw and Hermes where an agent has to run permanently and remember what it learned. Custom Python or Node where no connector exists. The choice follows the job, not a preference.
Where should we start if nothing is automated yet?
Start with the process that costs the most hours and has the clearest rules, not with the most exciting one. In most companies that is lead intake or invoice handling. We map your processes in an audit first, then automate the one with the shortest payback, so the project funds the next step.
Will automation replace people on our team?
No, in our projects it removes the work nobody wanted. The realistic outcome is that the same team handles more volume without extra hires, and spends its hours on client conversations rather than on retyping data between systems. We tell you before the build which tasks disappear.
Who owns the automations you build?
You do. The workflows run in your accounts and on your infrastructure where self hosting is used, and you keep full access and full documentation. There is no vendor lock in and no situation where leaving us means the automations stop working.
How long does an automation project take?
A single connected flow is usually live within one to two weeks. A process involving AI judgement steps takes three to six weeks including testing, because it has to be checked against real cases, not demo data. Autonomous agents take longer, since they need supervised running time before they are trusted alone.