LLMs and API integrations
Summarising, classifying and extracting information from text using an appropriate model and structured output.
IGTCODE Services Serbia
AI integrations for business systems and applications
IGTCODE in Serbia integrates AI models and services into business software, web and mobile apps. An AI integration connects models with real data, permissions and tasks within a system, rather than simply adding a chatbot.
Where can AI help?
We start with a repetitive task and a clear definition of a useful result. We test representative examples before expanding to the whole process.
AI assistants
Finding information in approved sources and preparing suggestions while respecting the user's existing access.
Data analysis
Helping interpret data and prepare summaries, with facts and calculations checked through reliable program logic.
Computer vision
For image-based tasks, we assess models for recognition or information extraction and evaluate quality using examples from the actual environment.
AI workflows inside existing systems
The backend prepares data, calls the model, validates output and passes results to the next step. Models receive limited tools and access. Important business decisions and irreversible actions may require human approval, with predefined error handling.
Security, privacy and quality
We define which data may leave the system and how usage is recorded. API keys stay on the backend. Model output is treated as untrusted input requiring validation. AI does not change authorisation rules or automatically gain access to every document.
Cost control and reliability
We monitor call volumes, limit input and output length and select models for the task. Caching and background processing are used where data freshness permits. We plan spending limits, service interruptions and a fallback workflow without an AI response.
Technologies and tools
We choose technology around the requirements and existing system. The specific stack and each service's role are agreed during planning.
How does development work?
Choose the task
Define inputs, acceptable results and automation boundaries.
Prototype and evaluate
Check quality against real and edge-case examples.
Integrate the backend
Connect authorisation, data sources, validation and the app.
Monitor operation
Measure errors, usefulness, response time and usage.
Questions before we start.
Is an AI integration the same as a chatbot?
No. A chatbot is one possible interface. An integration can process a document, prepare a report or assist an employee inside an existing system.
Do you develop your own large language model?
For business integrations, we start with suitable existing models and AI services. Developing or adapting a dedicated model is considered only where requirements justify it.
Can AI use internal documents?
Yes, with clearly defined sources and permissions. We agree which information can be sent to a service and ensure users can access only authorised content.
Can an AI model make mistakes?
Yes. We evaluate representative examples, validate outputs and define when a person must review the result. AI responses should not be treated as guaranteed facts.
How are AI service costs controlled?
We measure calls and data volumes, choose models for the task and define usage limits. Third-party service charges are separate from development costs.
Can AI be added to existing software?
Yes, where the architecture and available APIs allow it. We first check data access, authorisation and a suitable place for the new workflow.
Related services
In practice
Projects behind the work.
Digital system for an association
Mensa Serbia
Membership, events and communication connected with administration through a shared mobile and web platform.
- Platforms
- Mobile app · Web · Administration
- Technologies
- Flutter · React · MySQL · REST API
Next step
Let's define
your project.
Tell us what it needs to do, who will use it and what matters most to you. Together, we will clarify the scope and propose the next step.