Business Digitalization

It covers moving manual or paper-based processes into digital systems - think custom software, automated workflows, internal tools, and integrations between the systems your business already uses.

We start with a discovery phase to map your current processes and identify where manual work creates the most friction or cost, then prioritize digitalization based on impact versus effort.

Both, depending on what fits best. Sometimes an existing tool solves the problem efficiently. Other times your process is specific enough that custom software delivers better long-term value.

Yes, in many cases the most cost-effective path is connecting your existing systems through integrations and automation, rather than replacing tools your team already knows how to use.

Timeline varies widely depending on scope - a single automated workflow might take 3 to 4 weeks, while a broader digitalization initiative across multiple processes can take several months.

Yes, we include onboarding and training as part of the rollout, so your team understands how to use the new tools confidently from day one, not just how they were built.

Yes, we offer ongoing support to handle bug fixes, adjustments as your processes evolve, and new automation as additional opportunities are identified.

Business digitalization starts from $15,000. The price moves with the number of processes and roles, the systems to connect and the state of their APIs, the data to clean and move, and the documents and approval routes to rebuild. When the work grows into a full system, a custom CRM starts from $30,000 and an ERP from $50,000. The final price is set after a strategic session, and its $500 is credited toward the project within 30 days.

Before development we record the current state of the process: how many cases a month, how long each takes, how many errors, how many days it takes to close the month. Together we agree which of these should change and by when. After the agreed period we measure the same things again. We do not promise savings in advance; the numbers before and after are the result.

We treat them as evidence. A spreadsheet the team has kept alive for years usually holds rules the official system does not know. We interview the people who maintain such files before designing anything, carry their rules into the new system, and ask the same people to check during training that nothing was lost. Only then is the file retired.

Parts of them, when the foundation is ready. AI needs current software, data it can reach through an API and clear limits: which records it may read, which actions need a person to confirm them, and how every change is logged. On an old system the first step is often an upgrade. We start with one measurable task, such as first replies to requests or call summaries, and scale only after it works.

Process by process. Each flow is built on a closed test copy, checked by your team, and taught on your own data. Then the old and new ways run side by side for a short period, and the old way is switched off on a date agreed in advance. One person on your side makes decisions, so the rollout does not wait for everyone to agree on everything.

The code, the deployment commands, the server requirements, a rollback procedure and an AGENTS.md file that describes the structure, the rules and the commands, so another team or an AI coding agent can continue the work. If you are unsure who controls your current domains, accounts and data, a digital ownership and debt audit, from $1,000, answers that before the project starts.