AI Process Automation for Companies in Romania
We automate business processes with AI for companies that want measurable results, not experiments: we pick the right use cases, implement them with clear data rules, and track the gains in hours and costs saved.
Get in TouchWho this service is for
CEOs, operations directors, and IT managers at companies in Romania come to us with the same problem, seen from different angles: teams losing hours on data entry, invoice checks, or answering the same requests over and over, while employees are already using ChatGPT on their own, with no rules for company data. The trigger is usually one of three things: leadership asking for an AI plan, an automation project that never made it past the pilot stage, or a workload growing faster than the team.
What is included
- Use-case analysis — A list of processes assessed by volume, error frequency, and data sensitivity, with the estimated gain for each and a clear recommendation on what to automate first.
- RPA and LLM-based automation — Automated workflows that use the right technology for each case — RPA for repetitive, well-defined steps and language models for documents, emails, and unstructured text — integrated into the systems you already use.
- AI assistants and agents — AI assistants built on your company's documents and procedures that answer questions from internal teams or customers, and pass any case that falls outside the agreed rules to a colleague, with the full history preserved.
- Governance and data protection — Written rules on which data may reach an AI model, where it is processed, and who validates the results, aligned with GDPR requirements and easy to explain to an auditor.
- AI adoption programs for teams — Hands-on training for users and developers with tools such as ChatGPT, Claude Code, Cursor, or GitHub Copilot, applied to your team's real tasks rather than generic examples.
How we work
- Discovery workshop
Over one to two weeks, we work with your teams to review candidate processes, measure the time they take today, and choose one or two cases with the best payoff for the effort.
- Pilot on a real process
We build the first automation in four to eight weeks, on real data, with human review of the results until accuracy reaches the threshold we agreed with you.
- Scale-up and integration
Once the pilot is validated, we move the automation into production, integrate it with your ERP, CRM, or email, and add the next processes in monthly cycles.
- Measurement and adjustment
Every month, we report the hours saved, the errors avoided, and the running cost of each automation; anything that does not justify its cost is adjusted or switched off.
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Frequently asked questions
Which business processes should we automate first?
The repetitive ones with high volume and clear rules: processing invoices and orders, reconciliations, recurring reports, sorting emails, or answering frequently asked questions. A good first process takes up measurable time every day, has its data available in digital form, and does not involve decisions carrying significant legal risk.
Does our data stay in the EU?
Yes, if that is your requirement, and we settle it from the start. We use AI services hosted in data centers within the European Union, or models running on the infrastructure you choose: ours, yours, or an EU cloud. We configure the services so that the data you send is not used to train models. Every data flow is documented for your GDPR records.
What is the difference between RPA and AI automation?
RPA follows fixed steps, exactly as an operator would: it copies data between applications, fills in forms, and generates reports. Automation with language models understands unstructured text, such as emails, contracts, or scanned invoices. The best results usually come from combining the two: AI extracts the information, and RPA enters it into the system.
How much does AI process automation cost?
It depends on the complexity of the process, the number of systems involved, and the volume of documents. You receive a firm quote for the discovery workshop and a separate estimate for the pilot, together with the expected gain, so you can decide whether the investment is justified before you start.
How do we measure whether automation was worth it?
Before the pilot, we measure the baseline: time per transaction, error rate, and processing turnaround. After launch, we compare the same indicators every month and factor in the running cost, including AI service usage. The result is a return-on-investment calculation you can present to leadership.