Voice-Activated Shopping Assistant Development

Implementation of optimized models like OpenAI's Whisper for high-accuracy transcription in noisy environments, ensuring reliable product search and command recognition. We fine-tune for retail-specific vocabulary and accents.

Deployment of domain-specific SLMs (e.g., Phi-3.5, custom-trained) for on-device or low-latency cloud intent classification and product query understanding, reducing dependency on large, costly LLMs for core functions.

Integration of voice fingerprinting and secure authentication protocols to enable hands-free reordering and account access, built with privacy-preserving techniques to protect customer data.

Architecture of a low-latency Retrieval-Augmented Generation (RAG) pipeline connected to your live product catalog and inventory system, ensuring voice responses are accurate, up-to-date, and contextual. Learn more about our approach in our guide to Retrieval-Augmented Generation (RAG) Infrastructure.

Development using cross-platform frameworks (e.g., for Alexa Skills, Google Actions, in-car systems) with a unified core logic layer, ensuring consistent functionality and faster deployment across all target voice channels.

Robust backend engineering for seamless integration with your Order Management System (OMS), CRM, and payment gateways using event-driven architectures and resilient API design patterns. This ensures voice actions trigger real business processes. For complex backend orchestration, explore our work on Agentic Workflow Design and Integration.