AI & automation
AI automation for the work between your systems.
Business automation, CRM integrations and AI implementation for defined operational tasks. Connect systems without hiding the rules or the exceptions.
See what happens to the difficult cases.
Run example requests through validation, an AI classification step and the CRM record, including a repeated request, a provider timeout and an uncertain classification. We distinguish accepted, queued and completed work, so each case ends in a state your team can act on.
What the example shows
- A repeated request is recognized by its identifier and creates no second record.
- A provider timeout is retried with a delay and a limit, then queued for a person.
- An uncertain AI classification becomes a draft that a person approves.
- A request is complete only when its record is confirmed in the CRM.
- RequestReceived with its identifier
- ValidateFields and identifier checked
- AI classificationTopic and confidence
- CRM recordWritten once, then confirmed
Exception queue1
A repeated request, recognized by its identifier. No second record.
From step 2
- Quote request, sent again
Retried then queued1
A provider timeout, retried with a delay and a limit, then queued.
From step 3
- Support request
Awaiting approval1
An uncertain classification, drafted for a person to approve.
From step 3
- Refund question
Completed3Validated, classified and confirmed in the CRM.
After step 4
- Quote request
- Order question
- Delivery question
Illustration: example requests travel along four numbered stations, the request, validation, an AI classification and the CRM record, and end in one of four trays: the exception queue, retried then queued, awaiting approval or completed.
What teams automate first.
Good first candidates repeat often, cross a few systems and have an owner who can say what a correct result looks like.
Lead capture and follow-up
Useful requests reach the right person with their context intact, and a visible fallback owner catches the ones no rule fits.
View Lead capture & follow-upOrder and inventory sync
Storefront, inventory and fulfillment records share stable identifiers, with a way to reconcile differences.
View Order & inventory synchronizationSupport requests
Routine questions are answered from approved knowledge, while sensitive or unclear cases reach a person with the context to act.
View Customer support automationRecurring reports
Agreed measures come together automatically, with their definitions, sources and freshness kept visible.
View Reporting automationOne enquiry, end to end
Follow an enquiry through validation, routing and recovery, and the decisions that keep the workflow accountable.
See the walkthrough: Lead workflow walkthrough
Choose the degree of automation the task can support.
Reliable flows, repeatable rules and probabilistic AI outputs need different controls and review points.
Put an AI assistant on a bounded task
An AI assistant can help with a bounded task when data access, output checks and escalation are explicit. We test it against representative cases and failure modes before placing it in an operational flow. A human remains responsible for consequential decisions.
View AI agents & assistantsConnect your CRM and business systems
CRM and API integrations transfer agreed facts between tools, with identifiers, ownership and failure handling defined. A successful request is not enough; duplicates, delayed messages and mismatched records need an operational answer.
View CRM & API integrationsBuild a visible n8n workflow
n8n makes a repeatable sequence visible while its rules stay understandable. We define triggers, authorization, retries and monitoring, then test what happens when a provider is unavailable.
View n8n automationKeep automations dependable
Find failures early and manage changes without losing track of what already ran. A retry is a business decision, not a default button.
View Automation maintenance
Make the rule clear before automating it.
An automation can move information quickly while still moving the wrong information. Before anything is built, we answer four questions about the process. The answers set the boundary for API integrations, rule-based workflows and AI-assisted tasks, and they sometimes show that a simple process change beats another tool.
Who starts the process?
The person, form or system event that begins the work, and what it must contain.
Which system holds the reliable record?
The source of truth for each fact, so two tools do not quietly disagree about it.
What must a person approve?
The decisions that stay with your team, and who signs them off.
How does an exception come back?
The route a failed or uncertain case takes back to someone who can resolve it.
The workflow platform and AI models we work with.
We build visible workflows with n8n and work with OpenAI, Claude, Gemini and Perplexity models. Model choice follows the task, data and provider terms; usage charges are separate.
Workflow platform
n8n
Workflow automation for repeatable processes whose rules stay understandable to the people who operate them.
View n8n automation
AI models
OpenAI, Claude, Gemini and Perplexity
Language models for classification, drafting and answers from approved sources, evaluated against the task before they reach a customer.
View AI agents & assistants
Questions to settle before data moves.
We settle these with you before any production data is connected, because an invisible chain of tools leaves a business unable to explain its own outcomes.
What information may the workflow process?
Where may that information be sent?
How long is it kept?
Who can correct a bad result?
Do regulated or confidential records need additional review?
Which provider usage charges and API limits apply?
Provider usage charges and API limits are separate from implementation work.
Read before you scope.
Four guides for the decisions behind an automation project: reliability, the choice of tool, cost and AI evaluation.
Keeping business automations reliable
Explicit state, duplicate handling, bounded retries and a human route for uncertain outcomes.
Read the guide: Keeping business automations reliablen8n vs Make vs Zapier for your workflow
Compare the tools on your own workflow, its connectors, governance and who will operate it.
Read the guide: n8n vs Make vs Zapier for your workflowWhat does n8n implementation cost?
The rules, integrations, reliability needs and operating model that drive the estimate.
Read the guide: What does n8n implementation cost?Evaluating an AI customer assistant
Representative questions, access boundaries and escalation, tested before customers rely on the answers.
Read the guide: Evaluating an AI customer assistant
Bring one process, including its difficult cases.
A concrete example is enough to start. No credentials or customer records are required in an initial enquiry.
What to bring
Where the request starts
The systems it touches
The people involved
The point where work stalls
Cases that need a correction or an exception
When important facts are still unknown, a short discovery or assessment stage comes first, so the scope rests on facts.
From there we identify a narrow first flow, its acceptance checks and the manual fallback it needs.
Some of the teams we have worked with.
Across talent, fitness, mobility, payments and local commerce.Questions about AI automation.
Should we automate a process that changes often?
Usually the rules need to be stabilized first. We can map the decisions, identify a bounded repeatable part and keep uncertain cases with a person. Encoding a moving policy in software may make change slower and errors harder to see.
Can AI act without a human review step?
That depends on the task and the impact of a wrong result. We begin with bounded inputs, evaluation cases, logging and a clear escalation path. A high-impact decision needs stronger controls and may remain human-approved even if AI helps prepare information.
Which AI models do you work with?
We work with OpenAI, Claude, Gemini and Perplexity models. The choice follows the task and the data involved, and each provider’s terms, data residency and retention are checked against your policy before customer data is sent.
Does every automation need n8n?
No. n8n fits when a workflow’s rules stay understandable to the people who operate it. A complex transaction may belong in application code, and a smaller rule inside a system you already use may be more reliable than another moving part.
Are AI provider charges part of the price?
Provider usage charges and API limits are separate from implementation work. Your proposal lists the services that apply and who holds each account.
Continue exploring
Continue exploring
Bring one process. We’ll map its difficult cases with you.
Describe where it starts, the systems it touches and where it stalls. We can propose a narrow first flow, its acceptance checks and the manual fallback it needs.
Technology names and marks belong to their owners.