Search across documents
Find relevant information in approved manuals, catalogs, help content, or internal documents.
I add AI features to web and mobile products.
That may mean document search, summaries, classification, drafting, or an assistant inside software your team or customers already use.
- Built around a real use case
- Review where it matters
- Usage and cost considered
AI is useful here when
People search the same material repeatedlyThe answers are in manuals, product documents, support notes, or internal knowledge.
Long inputs need a first passEmails, forms, or documents need summarizing, sorting, or turning into a draft.
The feature belongs inside a productUsers need the result in the same app where they already do the rest of the work.
Useful AI features I can build
Summaries and drafts
Turn long requests or documents into a useful first pass that a person can review and edit.
Classification and routing
Sort messages, leads, tickets, or records and send them to the right next step.
Assistants inside a product
Add an AI-assisted flow to a web or mobile application instead of making users switch tools.
AI inside a real product
AI planning in Mappu
Mappu uses AI inside a broader travel product, connected to maps, saved places, user choices, and generated audio content.
How I approach an AI feature
Start with real examples
I look at representative inputs, the result people need, and the mistakes that would matter.
Define what the feature should do
We agree on useful outputs, review points, source material, and cases the software should hand back to a person.
Build it into the product
I connect the model or service to the interface, data, permissions, and existing workflow.
Test quality, speed, and cost
We test representative cases and check whether the feature is useful enough to justify running it.
Questions about AI projects
Can you add AI to an existing product?
Yes. I first check where the feature belongs in the current user flow and what data, permissions, and interface changes it needs.
Which AI provider do you use?
It depends on the task, data, budget, and existing stack. Before production, we agree on the provider, where data is processed, and what is stored.
How do we know whether AI is needed?
We start with the result you need. If normal software or a simpler automation can do the job more reliably, that is usually the better choice.
Can users review the result?
Yes. For drafts, summaries, recommendations, or business decisions, the product can include review, editing, source links, or approval before the next step.
How are usage costs controlled?
We can set limits, choose smaller models where they are enough, track usage, and design the feature so expensive calls happen only when useful.
What are you trying to build?
A short outline is enough. Tell me what exists, what is getting in the way, and what you would like to have working.