Automations for work you still do by hand: copying, repetitive decisions and tasks that slow the team down every day. One process is PLN 5,000-15,000 net; a multi-agent system is PLN 20,000-80,000 net. We design workflows that connect AI, APIs, CRM, ERP, emails and documents into one controlled system. The goal is not a flashy chatbot. The goal is fewer hours, fewer errors and faster information flow.
TL;DR: One process is PLN 5,000-15,000 net; a multi-agent system is PLN 20,000-80,000 net.
Who it is for
For companies with repetitive operational work that want to recover time without adding more headcount.
Scope
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.
Automatic email and form processing
Reports generated without manual work
Data synchronization between systems
Alerts, statuses and retry logic for process errors
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 unique path absorbed from the old AI-implementation page: 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.
Search intent
This page designs a daily workflow that moves fields, retries failures and calls a human on exceptions. Diagnosis stays on the audit page. The path from prototype to production now lives here: a small working slice first, then integrations and monitoring.
Next step
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
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. Proxy Poland is the in-house example: payments, provisioning and rotation run as a system, not as a person pasting access after every checkout.
If the question is "should we do this at all", that is the audit. If the question is "how do we go from a prototype to production with roles and training", that is AI implementation. If the data lives in Comarch or Symfonia and the job is a write-back, that is the integrations page.
This URL keeps the workflow: map, build, measure, 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.
Free 30-minute consultation. We'll come back with a proposal within 24h.