Services
AI Development & Automation
AI features with a clear job to do — from speech and translation to document workflows, summaries and useful automation.
A good fit when you have a specific information task that AI could help someone complete, review or understand faster.
Tell us what you are working onWhat this can include.
We use AI where it genuinely makes a task easier or faster. The work starts with the problem and the source information, not with adding a chatbot because AI happens to be popular. Provider credentials stay on the server, and people should have a sensible way to review or correct important output.
The exact scope depends on the product, the team and what already exists. These are the areas we can bring into the project when they are useful.
- LLM integrations
- Speech-to-text and translation
- Summaries and extraction
- Grounded question answering
- Workflow automation
- Private data handling
How we usually think about it.
- 01
Start with the task, not with 'we need AI'
We look at the input, the useful output and who needs to review the result. Transcription, extraction and question answering are different problems. A focused workflow is easier to test than a general chatbot with no clear purpose.
- 02
Give people a way to check the result
If an answer matters, the person using it should have context for where it came from and a sensible way to correct or reject it. We plan those review points alongside the feature itself.
- 03
Treat model access like any other backend dependency
Provider credentials stay on the server. We plan data flow, failure handling, access rules and provider costs before choosing the final integration.
A real example
Oralyvo
A WianTribe product · Live
Oralyvo turns a transcript into summaries, translations, questions and next steps. Its case study explains how provider credentials stay server-side, how multiple transcription engines are used and how answers are grounded in the recorded conversation.
Read the Oralyvo case studyA couple of common questions.
Do you train a new model for every AI project?
No. The work shown here uses existing AI and speech services inside a product. We first ask whether those tools, or even a simpler rule-based approach, are enough for the job.
Can an AI workflow run without human review?
Sometimes, but that depends on the task and what happens if it is wrong. We make review and approval points an explicit product decision rather than assuming automation is always better.
Let’s talk
Got something you're trying to build?
You do not need a finished brief. Tell us what you are working on, what is not working yet and what you would like the product to do. We can take it from there.