T.I. PRODUCTION / AI
AI development tied to a measurable use case
We integrate LLMs, voice, translation and automation where they reduce manual work or unlock a new product experience.
PRODUCT ENGINEERINGAIStrategy · UX/UI · Build · Launch
What is included
We do not start with “which model should we use?”. We first define the process, cost of error, latency, data constraints and expected outcome. Then we select the architecture: cloud or local models, RAG, speech pipelines, queues and system integrations.
- LLM and OpenAI-compatible API integrations
- Speech-to-text, text-to-speech and real-time translation
- RAG and retrieval over internal knowledge
- AI agents and repetitive workflow automation
- Local and hybrid scenarios for privacy and resilience
PROCESS
How we work
UX/UI and prototype
Development and integrations
Testing, launch and analytics
FAQ
Frequently asked questions
Can you add AI to an existing product?
Yes. We usually begin with one measurable use case and integrate it through APIs without rewriting the whole product.
Can you run local models?
Yes, when the hardware and quality constraints make sense. Hybrid local/cloud architecture is often the best trade-off.
How do you control AI quality?
We define test cases, logging, fallback behavior and quality metrics around the actual business task.
Discuss a project
We integrate LLMs, voice, translation and automation where they reduce manual work or unlock a new product experience.
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