Business process automation that gives your team its hours back

Automation does not have to be a large transformation program. In most companies, removing the three or four steps that eat the most time is enough to change how the week feels. The work we automate most often:

• Spreadsheet automation: merging files from different sources, cleaning data, catching formula errors and producing one consistent report.
• Reporting automation: pulling sales, inventory, finance or ad data on a schedule and delivering it by email or on a dashboard.
• Data sync between systems: ending manual copy-paste between your online store, accounting software, CRM and shipping provider.
• Document and email processing: reading incoming invoices, order forms or applications and entering them into the right system.
• Alerts and approval flows: notifying the right person when stock runs low, a payment is late or a request is waiting for sign-off.

Every automation leaves a clear log a person can review, so you always know what ran, when, and with which data.

Traditional workflow automation runs on rules: "if this column says X, do Y". But a lot of real-world input is messy: free-text emails, scanned documents, supplier price lists that arrive in a different format every month. That is where we place language models such as Claude and Gemini inside the workflow.

Classifying incoming customer emails, extracting totals and tax IDs from PDF invoices, or writing a short management summary of a long report can now be automated dependably. We use AI only in the steps where it makes a real difference, keep important decisions behind human approval, and design the flow so model costs stay predictable.

A fixed list price for automation would be misleading, because two companies asking for "report automation" can need very different things. The main factors are:

• How many systems need to be connected, and whether they offer an API
• How clean the data is, and how much matching and cleaning it needs
• The number of steps in the workflow and the exceptions it must handle
• Whether AI is needed for any step
• Whether you need an admin dashboard or a service that simply runs in the background

After a short call we send a free quote. We can scope anything from a single-purpose script to a full multi-system workflow, and we usually recommend starting with the step that saves the most time, then growing from there.

Automating a single workflow typically takes 1–3 weeks from kickoff to production. Broader projects that connect several systems and include a dashboard with user roles usually take 4–8 weeks.

We build with Node.js and TypeScript services, scheduled jobs, Firebase or a similar cloud database, and admin dashboards deployed on Vercel. Google Sheets, Excel files, mailboxes, accounting and e-commerce APIs, and the Claude and Gemini models are the pieces we connect most often. The code lives in a repository you own, documented and handed over.

Weras Labs is a small, senior software team led by founder Habip Dayan. We build and ship our own software products, so we know what it takes for code to run in production for years: monitoring, clear error reporting and maintainable structure.

Throughout the project you talk directly to the developer who writes the code, not to an account manager. We are based in Turkey and work with clients abroad remotely, in English, with the same process.