AI Integration
What is AI integration?
AI integration means embedding model-powered capabilities into existing applications and systems — LLMs, RAG, assistants, speech pipelines — designed so AI can draft or assist while deterministic checks and human approval gates protect consequential actions.
Case Studies
Real architectural decisions and production trade-offs. We don't invent case studies — these are actual engineering records.
How we build this
We don't invent case studies. Below are actual technical implementations and product records built by Vasiva that demonstrate this capability in production.
talkbetter
Vasiva Product Case RecordThe Problem
Spoken English evaluation for engineering students breaks down on unstable networks when uploads are naive.
Constraints
- Edge/unstable networks
- Reliable media upload
- Honest scoring pipelines
Approach
Chunked recording, local cache, backoff upload queues, and evaluation that does not assume perfect connectivity.
Architecture
MediaRecorder → IndexedDB cache → upload queue → signed storage → evaluation.
Implementation & Outcome
Shipped product with speech evaluation paths documented in engineering notes.
Production speech product usable beyond ideal office Wi-Fi conditions.
Engineering Lessons
- Network reality is part of product architecture
- AI features need boring infrastructure
Original Vasiva decision assets
About AI Integration
Use AI integration when you already have working products or systems and need model-powered capabilities inside them — assistants, RAG, speech, or drafting flows — with verification and human gates on consequential actions. Prefer consulting-first when the opportunity, risk, or architecture is still unclear.
Ready to embed AI into existing systems?
Select engagements. You work with the engineers who ship Vasiva products.