I am an AI product and technology leader at Accenture Song, building privacy-conscious AI products and platforms at the intersection of enterprise strategy and hands-on engineering. I lead product and technology for an internal AI venture, serve as the platform's global representative, and remain hands-on in architecture and critical engineering decisions.
My background spans 16+ years across software engineering, entrepreneurship, consulting, and multidisciplinary product leadership. I specialise in turning emerging AI capabilities into production platforms, scalable delivery models, and useful customer experiences.
I also build local-first AI tools for sensitive, messy human information. They make capable models practical without making cloud upload the default.
Local, offline transcription and speaker identification for Apple Silicon. It combines multilingual speech recognition, speaker diarization, voice embeddings, and cross-file identity matching without uploading recordings to a hosted transcription service.
What it demonstrates: a resilient multi-model pipeline, local AI acceleration, privacy-aware product design, and usable outputs for real research, meetings, and media workflows.
Local AI image naming for macOS Downloads folders. It uses a vision-language model through Ollama to produce useful filenames while keeping image data on the device.
What it demonstrates: safe automation around an untrusted model, durable local state, macOS integration, and an intentionally simple product experience.
- Enterprise AI product and technology strategy
- Agentic workflows and production LLM systems
- AI-powered content production
- Multidisciplinary product and engineering organisations
- Technical pre-sales and enterprise customer delivery
- Local and privacy-conscious AI