I look at the process, data, and cost of the problem, then build and deploy automation or software. We measure what changes.
Measured outcomes, not promises
Data points processed
Manual work eliminated
Faster reconciliation
AI-personalized emails
My work includes dispatcher automation, financial reconciliation, and B2B outreach. I handle the process analysis, development, and deployment, with a clear business goal to measure against.
I study Finance and Accounting at FINRA University. That background shapes how I assess costs, reporting, and potential return before recommending a build. If the numbers don't justify it, I'll say so.
You work directly with me, from the first review to the production handover. We agree the scope, deliverables, and price up front: a one-time implementation fee and fixed monthly maintenance.
I start with the process and the data, then scope the work around its expected impact. Every engagement is documented up front and covered by a confidentiality agreement.
Systems that take over the complex operational work. A process that used to eat 12 hours runs as an autonomous cycle in under 30 minutes.
Reliable external data collection for reporting, analysis, and automation. Production data pipelines tested past 10 million data points.
I build business websites and applications for everyday work, then connect them with the tools your team uses. Enquiries and data reach the right place without being copied by hand.
Before building, I map the process, identify bottlenecks, and review the data, KPIs, and reporting. I look at time spent, costs, and potential ROI to decide what is worth automating, what needs improving, and what can stay as it is.
I prepare and analyze data for forecasting, anomaly detection, classification, or segmentation. I use machine learning when prediction or pattern recognition helps solve the problem, and check it against a simpler approach before putting it into use.
I deploy systems to a VPS or cloud environment, with databases, scheduled jobs, monitoring, logs, and backups. Maintenance keeps them running reliably, with scaling when the workload calls for it.
Three client projects, with the problem, the build, and the measured result. Client identities remain confidential.
manual task reduction
Business problem
A US freight operator was syncing ride data across platforms by hand and filling weight tables one row at a time. Dispatchers lost 8+ hours a day to pure data entry.
What I built
Now one system syncs every platform in real time, fills the tables for weights, routes, and timings, and flags anything unusual for a person to check. The manual entry is simply gone.
faster reconciliation
Business problem
An accounting firm ran a 15-day reconciliation cycle. Staff scanned documents by hand and keyed the data back into the accounting software, hundreds of hours every month.
What I built
An OCR pipeline now reads the documents, pulls the data, and fills the accounting software itself. A person only steps in when something gets flagged.
more outreach capacity
Business problem
A B2B agency was stuck at 100 personalized emails a day, written by hand and sent whenever someone had a free moment. The only way to send more was to hire more.
What I built
A custom n8n system handles the personalization and the scraping. It sends 1,000 targeted emails a day, runs the follow-ups on its own, and hands real replies to a person.
Analyze the problem, design and build the solution, deploy it, then measure and improve. You see working software early and own everything that ships.
We sign a mutual NDA, map the process and data, and measure the time and cost involved. We agree on KPIs and estimate the potential return before committing to a build.
I choose the approach around the problem: automation, custom software, or machine learning where useful. You test a working prototype on your own workflow and data.
The system goes into production with the required database, scheduled jobs, monitoring, and backups. Documentation, handover, and team onboarding are part of the rollout.
I monitor reliability and compare the agreed KPIs with the starting point. We use those results to choose the next improvement, with support and maintenance defined before launch.
For a clearly scoped automation, the usual target is a prototype in 7 days and production in 15–30. We confirm the schedule after reviewing your data, integrations, and requirements.
One implementation fee and fixed monthly maintenance. Before launch, we agree what support covers, incident priorities, response times, and recovery steps.
A mutual NDA, documented handover, and ownership of the delivered code. Your team knows what was built, how it runs, and how to maintain it.
The things prospective clients ask before the first call.
For a clearly scoped automation, the usual target is a working prototype in 7 days and production in 15–30. We confirm dates after reviewing your data and integrations. Larger builds or data preparation may need more time.
A one-time implementation fee, followed by fixed monthly maintenance. The scope, deliverables, and ongoing costs are agreed before work starts.
Every engagement starts with a mutual NDA. Your data, credentials, and results stay yours, permanently. Confidentiality is the default here, not an upsell.
Dispatcher and logistics data entry, OCR-based financial reconciliation, high-volume B2B outreach, large-scale web scraping, and custom internal dashboards and portals.
Yes. I review the process, available data, reporting, and costs to identify the problem and estimate the potential impact. The first step may be better data or a simpler process rather than new software.
When prediction or pattern recognition is useful, such as forecasting, anomaly detection, or classification. I first check whether the data is suitable and whether a simpler method would do the job.
Yes. The practice is remote-first and available worldwide, based in Bosnia & Herzegovina.
Maintenance includes the agreed 7-day issue-resolution window. Before launch, we define how incidents are reported, their priority, response times, and recovery steps. Requirements for critical operations are part of that agreement.
For project briefs, consultation requests, or long-term partnerships.
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