Process automation
Automations for work you still do by hand: copying, repetitive decisions and tasks that slow the team down every day. We design workflows that connect AI, APIs, CRM, ERP, emails and documents into one controlled system. The goal is fewer hours, fewer errors and faster information flow.
One process is PLN 5,000-15,000 net. A system with several agents is PLN 20,000-80,000 net.
Pricing
Automation of one process costs 5-15k PLN. A system of several interlocking processes costs 20-80k PLN. This scope is the flow and integrations: a process map, a mail or CRM hook and measurement after the sprint - not a site widget and not helpdesk tickets.
As-is map, workflow, mail or CRM hook and measurement after the sprint. Deployed in a few working days.
When one workflow is not enough: orchestration, ERP/CRM integration and context memory.
| Channel | Deployment cost | Deployment time | What it handles |
|---|---|---|---|
| One process | 5-15k PLN | A few working days | As-is map, workflow, mail or CRM hook and measurement after the sprint |
| Multi-agent system | 20-80k PLN | When one workflow is not enough | Orchestration, ERP/CRM integration and context memory |
A quote after you point to the manual chain the team repeats every week. Prices current as of August 2026.
Who it is for
For companies with repetitive operational work that want to recover time without adding more headcount.
Process mapping, workflow design, AI automation, API integrations, status dashboards and error handling.
Outcomes
A well-chosen automation process usually shows value after the first sprint: less copying, shorter response time and more predictable operations.
Process
We document who moves data, when it happens and which decisions can be automated safely.
We choose the right tools: code, n8n, APIs, AI agents, RPA or a hybrid. The tool follows the process, not the other way around.
We launch the process and measure execution time, errors and manual interventions.
From prototype to production
The path is a small prototype on real data, then integrations, roles and monitoring. Whether to start at all stays on the AI audit.
We pick the process where AI pays back: repetition, time cost, error risk and available data. The model comes after that choice.
We build a small version on real emails, documents or records. After a few days you see quality, data gaps and whether to continue.
We add integrations, roles, logs, limits and team instructions. The result returns to daily work, not a chat window.
A production system shortens the whole chain, not just the generated text. A human stays on high-risk decisions. If quality drops, we shrink the scope - we do not add autonomy.
What we automate
We design a daily workflow that moves fields, retries failures and calls a person when something falls outside the rules. A small working slice comes first, then integrations and monitoring.
A well-chosen automation process usually shows value after the first sprint: less copying, shorter response time and more predictable operations.
The first workflow is the copy-paste chain you already run every week: mail to CRM, sheet to report, form to status. We map who clicks, then pick code, n8n or an API. The tool comes after the map.
A boring, measurable workflow
We automate the path a record already travels. A chatbot that answers visitors is a different page. A helpdesk agent that sorts tickets is a different page.
Who starts the task, where the file arrives, which field is retyped, where the result must land, and what a failure looks like. Until that is on one page, n8n, a custom worker or an AI extractor are guesses.
Hard fields stay in code and APIs: amounts, VAT IDs, order statuses, retry counters. Language and messy documents are the only place a model earns a seat. A single prompt that "does the process" is the architecture we refuse.
Inbound mail that should become a CRM row. A weekly report glued from three sheets. A form that should open a status and an alert. Those loops are frequent, bounded and easy to measure: time per case, retries, human edits.
We do not start with the process that stops the company if it fails. The first sprint has to be reversible. A good first process is one that already runs every week: a payment that should open access, a form that should update a status, a file that should become a report. A person should not paste the same result after every checkout.
If the real question is whether to automate at all, start with an audit. If the process is already chosen, we go from a small working slice to a live workflow with roles and monitoring.
We keep the workflow: map, build, measure, then add the next loop.
Process automation
Common questions about business process automation with ai - scope, deployment, data, cost and security.
Start with frequent, repetitive tasks with clear rules: inquiries, invoices, reports, order statuses, CRM updates and document classification.
Not always. Most often we add an integration and automation layer around the systems you already use.
No. AI is useful for language, documents and fuzzy decisions. APIs and rules are still best for structured data.
Next step
Point at the manual chain your team still repeats. We will return with a map of the first workflow and a price for that sprint, not for a company-wide program.
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