Distill vs Presto Voice

What users praise

• • Deterministic output: same input always gives same output, improving reliability.
• • No LLM calls during processing, keeping overhead low and costs predictable.
• • Persistent memory with hierarchical decay manages long-term agent context.
• • Semantic dedup with cosine thresholds reduces token waste effectively.

What frustrates them

• • No real user reviews or community feedback to validate claims.
• • Setup requires developer skills; not plug-and-play for non-coders.
• • Documentation and support channels are unclear in the data.
• • Name confusion with a video service may mislead potential users.

What users praise

• • Vendor claims up to 95% non-intervention on drive-thru orders, saving labor costs.
• • Claims an upselling engine with 88% offer acceptance and 6% revenue lift.
• • Runs a spectrum of Voice AI models to adapt to different menus and speech patterns.
• • Has 15+ years of restaurant-industry experience and national rollout references.

What frustrates them

• • No independent user reviews or community validation of the vendor's claims.
• • Brand name 'Presto' is confused with unrelated products like canners and transit cards.
• • App Store reviews for a similarly named app cite glitches, autoload failures, and connection errors.
• • Tourists report being locked out of the related Presto transit app without a Canadian address.