JioTranslate — AI-Powered Language Systems
Operationalizing reliable AI-driven language capabilities at scale
Context & Problem
As collaboration and communication products expanded across regions, language became a major barrier.
While AI-based translation existed, reliability, latency, and trust were critical challenges — especially in real-time and enterprise contexts.
My Role & Ownership
I led product strategy for AI-powered language systems, covering UX design, feature prioritization, accuracy metrics, and cross-platform consistency.
Constraints & Trade-offs
- Real-time performance requirements
- Language variability and contextual accuracy
- User trust expectations
- Balancing innovation with stability
Key Decisions
- Designed translation UX before model optimization
- Defined accuracy and latency metrics upfront
- Prioritized context-aware translation
- Ensured consistent experiences across platforms
Impact & Outcomes
- Delivered reliable real-time translation across products
- Built strong user trust in AI-driven communication
- Created a reusable AI foundation across use cases
What I Learned
AI earns trust through consistency and reliability, not novelty.
What I’d Do Differently Today
I would invest earlier in explainability signals to make AI behavior more transparent.