Process audit
We map the steps, participants, data sources and points where the team loses time or repeatedly encounters the same errors.
OUR APPROACH
WE SIMPLIFY THE PROCESS BEFORE WE AUTOMATE IT.
We do not add AI simply because it is fashionable. We identify where work repeats, which data enters the process, where human judgement is essential and where automation can create measurable value without removing control.
- We automate a defined process rather than an abstract idea
- Human approval remains wherever the level of risk requires it
- We connect the tools the team already uses
- We measure time saved, response speed and execution quality
FROM REPETITIVE TASK TO RELIABLE WORKFLOW
HOW WE WORK
Data and integrations
We establish which systems need to exchange information, which API connections are available and which data can safely be used by the AI model.
Logic and safeguards
We design the workflow, conditions, fallback scenarios, human checkpoints and rules that prevent incorrect or unwanted actions.
Build and testing
We connect the systems, configure the AI instructions and test real scenarios, edge cases, interruptions and the quality of the generated output.
Rollout and improvement
We release the automation in controlled stages, monitor its performance and improve the logic through real data and team feedback.
WHAT WE CAN AUTOMATE
AI AND WORKFLOWS BUILT AROUND REAL OPERATIONS.
01
Customer-facing AI assistants
Assistants that answer initial questions, guide visitors towards the correct service, collect context and hand over to a person when required.
02
Enquiry and lead processing
Qualification, categorisation, enrichment, assignment to the correct salesperson and automated follow-up actions.
03
Documents and content
Extracting, structuring, summarising and transferring information from email, forms, quotations, files and internal documents.
04
Internal AI assistants
Searching company knowledge, preparing answers, summaries, instructions and support for recurring operational work.
05
Connected systems
Automatic data exchange between CRM, CMS, email, calendars, databases, forms, payments and specialist business tools.
06
Alerts and operational control
Automated reports, warnings, reminders, status changes and tasks whenever a defined condition or event occurs.
AUTOMATION, AI OR AGENT
THE RIGHT MODEL FOR THE ACTUAL TASK.
Rule-based automation
Best for predictable steps with clear triggers and conditions — such as moving data, sending alerts, changing statuses and synchronising systems.
AI-assisted workflow
An AI model classifies, extracts, summarises or prepares content while the sequence of actions and business rules remain controlled by the workflow.
AI agent
Useful when the task genuinely requires choosing between tools or next actions. The agent operates within predefined permissions, boundaries and fallback scenarios.
HUMAN-IN-THE-LOOP
CRITICAL ACTIONS CAN REMAIN UNDER HUMAN CONTROL.
Automatic
Low-risk and predictable actions execute without intervention once the required conditions are met.
Approval required
The AI or workflow prepares the next step, but a person confirms it before execution.
Human escalation
When confidence is low, an exception occurs or an action carries more risk, the process is routed to the right team member.
BUSINESS LOGIC BEFORE AI
WE AUTOMATE ONLY WHEN THERE IS SOMETHING WORTH MEASURING.
Before automation
We measure how often the process runs, how long it takes, how many people are involved, where errors occur and which external systems are required.
After rollout
We track time saved, response speed, error rates, required human intervention and ongoing costs for APIs, hosting and external providers.
TECHNOLOGY
A MODULAR FOUNDATION CONNECTING AI WITH THE BUSINESS.
We select models and tools around the data, security requirements, complexity and required reliability. Our solutions most often combine:
01n8n
02OpenAI API
03LLM APIs
04Next.js
05Supabase
06PostgreSQL
07REST APIs
08Webhooks
WHAT TO EXPECT
LESS REPETITION. MORE CONTROL AND SPEED.
Time returned to the team
People no longer repeat the same transfers, checks and follow-up actions manually every day.
Faster response
Enquiries, alerts and internal tasks are handled immediately rather than waiting for a team member to become available.
A consistent process
Critical steps follow the same logic every time, while exceptions are routed to the correct person.
Visibility and improvement
Executions can be monitored, measured and refined instead of the automation operating as an opaque black box.
SELECTED WORK
A LOOK AT SOME OFOUR WORK.
Real projects built for different business models — from brand websites and online stores to web applications and interactive platforms.
View all projects
FAQ / AI AUTOMATION
BEFORE WEAUTOMATE.
Common questions before an AI automation project — from integrations and human control to data, recurring costs and measurable value.
Clear and repetitive processes are usually the strongest candidates: enquiry handling, lead qualification, document data extraction, internal alerts, follow-up actions, reporting and work spanning multiple systems. We first check whether automation creates meaningful value.
A standard automation follows predefined triggers, rules and steps. An AI agent can choose between permitted tools and next actions based on context, but it should still operate within clear permissions, boundaries and safeguards.
Yes, when the platform provides a suitable API, webhook or another supported integration method. Before development we verify technical limitations, access permissions and any third-party costs.
Not necessarily. In many cases the automation connects the tools you already use. If a system does not expose a reliable integration method, we discuss an alternative approach before development begins.
Yes. Actions can be divided into automatic steps, approval-required steps and situations that escalate to a person when specific conditions are met.
The architecture depends on data sensitivity and the providers involved. We limit access to what is required, separate permissions between systems and clarify which external services process information before rollout.
Potentially. External services such as AI APIs, n8n hosting or cloud plans, databases, email or SMS providers, voice providers, CRM systems and other APIs can have usage-based or subscription costs. These are kept separate from custom development.
We compare the current process with the post-rollout results: human hours saved, response speed, fewer errors and the amount of manual intervention still required. The objective is measurable operational impact rather than an AI feature for its own sake.