Services
AI Development & Automation
AI-powered workflows, conversational interfaces, transcription, automation, data intelligence and useful AI integrations.
For teams with a specific information task that AI can help people complete, review or understand.
Discuss your projectWhat we can build together.
AI features that earn their place: grounded in real data, honest about uncertainty and designed so people stay in control. Model access runs through secure server-side infrastructure, never the browser.
We agree the priorities and deliverables around your project. These are the capabilities we can bring into that scope.
- LLM integrations
- Speech-to-text and translation
- Summaries and extraction
- Grounded question answering
- Workflow automation
- Private data handling
How we approach the work.
- 01
Start with the task and its source material
We identify the input, the useful output and the person responsible for reviewing it. Transcription, extraction and question answering have different needs; a focused workflow is easier to assess than adding a general chatbot without a clear purpose.
- 02
Keep people in control
We consider how users check an answer against its source, correct a transcript or recover from an uncertain result. AI output needs clear context and a useful fallback. We scope evaluation around representative examples and the consequences of a wrong answer.
- 03
Treat model access as infrastructure
Provider credentials belong on the server. We plan data flow, access controls and failure handling alongside the interface, and discuss provider costs and data-handling requirements before selecting the integration.
From the portfolio
Oralyvo
A WianTribe product · Live
Oralyvo turns a shared transcript into summaries, translations, questions and next steps. Its case study describes server-side provider credentials, multiple transcription engines and answers grounded in the recorded conversation.
Read the Oralyvo case studyQuestions before we begin.
Do you train a new AI model for every project?
No. The work shown here uses existing model and speech services integrated into a product. We start by assessing whether those services, or a simpler rule-based approach, meet the need.
Can an AI workflow run without human review?
That depends on the task and the impact of mistakes. We discuss review and approval points explicitly. A useful prototype does not by itself establish that an automated workflow is reliable enough to act independently.
Start a Project
Have something worth building?
Whether you're starting with an idea, improving an existing product or looking for a development partner, we'd like to hear about it.