Text
Understanding and working with written information — emails, notes, messages and records.
- Classification
- Summarisation
- Extraction
- Search
- Assistants
AI Software Development in Ireland
Have a business problem where AI might help? Syfo can explore the idea and build the surrounding software required to make it useful in practice.
What modern AI can do inside software
Modern AI makes new kinds of software possible. We combine it with custom applications, databases, interfaces, integrations and business logic to create complete systems.
Documents
Turning documents people currently read and re-type into structured, usable data.
- Reading documents
- Extracting structured data
- Categorising information
- Searching document collections
Images & computer vision
Modern vision models can allow software to understand what is happening in images or video. This can create opportunities for monitoring, inspection, detection and other industry-specific applications.
- Image analysis
- Video processing
- Event detection
- Object recognition
- Visual classification
- Alerts and historical event data
Business processes
Using AI as one step inside a larger workflow, with people and rules around it.
- AI-assisted workflows
- Decision support
- Data processing
- Internal tools
The AI model is only one part of the system.
A model on its own isn't a product. To be useful in a business, it needs the software around it: somewhere for people to work, data to draw on, rules to follow and a way to check the results.
User interfaces
Authentication
Databases
APIs
AI model
Integrations
Alerts
Business rules
Reporting
Administration
Monitoring
Human review
When AI makes sense — and when it doesn't
Not every problem needs AI. Often a database, a form or a simple automation is the better answer, and we'll say so.
AI is often useful when…
- The input is unstructured — text, documents, images or video
- A person currently reads or looks at something to decide what it is
- Occasional errors can be caught by a review step
- There's enough volume for automation to matter
Conventional software is usually better when…
- The rules are clear and can be written down
- The data is already structured
- Every answer must be exactly right, with no review
- A database, form or simple automation would do the job
From idea to working system
- 01
Explore the idea
What should the AI do, what goes in, what should come out, and how will you know it's working?
- 02
Test it on real examples
A focused proof of concept using representative data, to see what accuracy is realistic.
- 03
Build the system around it
Interfaces, data, permissions, review steps and integrations — the parts that make it usable.
- 04
Monitor and improve
Track how it performs in real use and refine it over time.
Common questions
Does our business need AI?
Not necessarily. Many problems are better solved with conventional software, a database or a simple automation. We'll recommend AI only where it provides a useful capability that ordinary software can't.
What happens to our data?
That depends on the provider, the model and how the system is designed, and it's something we decide with you at the start. We consider what data is sent, where it's processed, how long it's kept and who can access the results.
How accurate will it be?
It depends on the task and the data. That's why we recommend testing on real examples before committing to a full build, and designing review steps where accuracy matters.
Can we start with a proof of concept?
Yes, and for most AI ideas that's the right first step. A small proof of concept shows what's realistic before you invest in the full system around it.
Have an idea where AI might help?
Tell us the problem. We'll help work out whether AI is the right tool, and what the software around it would need.