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 real inputs, the result people need, and the mistakes that matter.
Define what the feature should do
We agree on useful outputs, sources, review points, and when a person needs to step in.
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 typical cases and check quality, speed, and running cost.
Questions about AI projects
Can you add AI to an existing product?
Yes. I check where it belongs in the current flow and what data, permissions, and interface changes it needs.
Which AI provider do you use?
It depends on the task, data, budget, and stack. Before production, we agree on the provider, data processing, and storage.
How do we know whether AI is needed?
We start with the result. If normal software or a simpler automation does the job more reliably, that is the better choice.
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?
Tell me what exists, where you are stuck, and what needs to work. I’ll reply within two business days with a practical next step.