What Is Custom Software Development?
Custom software development means designing and building software around one organisation's workflow, data and systems, rather than adapting an off-the-shelf package. From Ankara, Hatson Tech builds web applications, internal dashboards, customer portals, APIs and cloud-based software infrastructure for organisations across Türkiye. The first question is always what the software must change: a slow approval path, repeated data entry, disconnected systems, or a product that cannot support its next stage.
What the Service Includes
- Enterprise web applications: Internal tools with role-based access, approval flows, reporting and audit trails.
- Dashboards and customer portals: Interfaces that replace scattered spreadsheets and email threads with a single view.
- APIs and integration: Stable, versioned and documented data exchange between ERP, CRM, accounting or field systems.
- Software infrastructure: Deployment, monitoring, backups, identity management and separate development, test and production environments, in the cloud or on premises.
- Modernisation of existing systems: Gradual restructuring of applications that have become hard to maintain.
- AI components: Where justified, controlled addition of capabilities such as document processing, search or forecasting. For assistants that take actions in your business systems, see AI agent development.
Custom Software or Off-the-Shelf?
Not every need calls for custom software. If you run a standard process, a packaged product is usually faster and less risky. The table below summarises the criteria we use to make the decision clear.
| Situation | Better fit |
|---|---|
| The process is standard in your industry and a package fits as is | Off-the-shelf package |
| A package is in use, but the team fills gaps with side spreadsheets and manual transfers | Package plus custom integration or module |
| The process is part of your competitive advantage and does not fit the package's model | Custom software |
| Data cannot leave the organisation and hosting rules are strict | Custom software or a package that can run on premises |
| Several systems must be joined into one flow | Custom integration layer |
| Per-user licence cost becomes a problem as you scale | Decide by comparing total cost of ownership |
We cover how this decision plays out for AI projects in our build or buy guide, and the options for renewing legacy systems in our application modernisation decision guide.
The Delivery Process, Step by Step
- Discovery: We map users, existing systems, data owners, integrations and exceptions. A reporting dashboard, for example, may depend more on the quality and timing of source data than on the dashboard framework.
- Scope and first release: A workflow map, an agreed narrow first release, measurable acceptance criteria and the risks to test early are written down. Our project scoping guide covers this step in detail.
- Architecture: We choose between a modular application, separate services, managed cloud components or a mix, based on real scale and team needs. Microservices are not an automatic improvement; they add deployment, monitoring and data consistency overhead.
- Development in short cycles: Working builds are shown at regular intervals and feedback goes into the next cycle.
- Testing and acceptance: Integrations, permissions, error handling and realistic data volumes are tested against the acceptance criteria before release.
- Release and operations: Deployment, monitoring, backups and an incident reporting and fix process are set up, and technical documentation is handed over.
- Maintenance and evolution: Usage and support feedback are reviewed together to decide the next improvements.
Quality, Security and Maintainability
The value of enterprise software shows not at first release but in being able to change it safely over the years. So we treat the following practices as the default in every system we deliver:
- Access control: The role and permission model is designed up front; who can see and approve what has the same answer in code and documentation.
- Audit trail: Who performed critical actions, and when, is traceable.
- Automated tests: The riskiest business rules are protected by tests, so changes do not silently break existing behaviour.
- Code review and version control: Every change is reviewed and can be rolled back.
- Documentation: Architecture decisions, setup steps and API contracts are delivered in writing, so another team can take the system over.
- Personal data: Retention, masking and access rules for personal data under KVKK and similar regulations are set at design time.
An API is valuable when another system or team needs a stable contract; authentication, versioning and error behaviour must be explicit. We document why each component exists so the system stays maintainable after launch.
Projects Run From Ankara
Our team is based in Ankara. With organisations in Ankara we can hold discovery workshops and acceptance meetings in person; for projects elsewhere, discovery, development and rollout can run remotely. Which steps happen on site and which remotely is written into the project plan from the start.
What Drives Cost and Timeline?
We do not publish a fixed price list, because the difference between two "dashboard" projects is rarely the number of screens; it is the rules and integrations behind them. The main factors are:
- The complexity of business rules and exceptions, and the number of approval and permission layers.
- How many systems must be integrated and whether they offer APIs.
- The volume and cleanliness of data to be migrated.
- Security, audit logging, data protection and hosting requirements (cloud or on premises).
- Number of users, concurrent load and availability expectations.
- Any need for mobile or offline use beyond the web.
- How available the people who decide and test on your side are.
After discovery these factors are itemised, so you can see which assumptions the proposal rests on. For questions to ask any software vendor, see our vendor selection guide.
What We Need From You
- A product owner who knows the process and can make decisions.
- A picture of today's workflow: existing spreadsheets, screen recordings, sample records or forms.
- A list of systems to connect and test access to them.
- Security, hosting and data retention rules.
- A few real users to take part in acceptance testing.
In data-driven products the state of the source data directly affects the timeline; our data readiness guide explains that side. If an AI feature goes into the product, it needs its own evaluation and human review path; adding a model does not replace reliable data and software.