Early speech models choked on short words like "OK." Direct audio processing raised accuracy to 97%, enabling complex automated bookings.
A conversational AI provider serving over 40,000 businesses processes more than 60 million calls for clients ranging from local clinics to national restaurant chains.
Standard button-based systems could not capture customer names, while early speech models stalled at 85% accuracy for short affirmations like "yes"...
“レストラン予約の際には名前を伝える必要がありますので、ボタンプッシュによる従来型の IVR では、やはり無理が出てきます。いずれ音声でのやり取りが必要になるだろうと予想していましたが、当初は技術的に難しく『待ち』の状態が続いていました。しかし 2023 年、自然言語でやり取りできる LLM（大規模言語モデル）や生成 AI が登場しました。これなら新たなシステムを開発できると判断して、早速導入しました。”
SaaS platform for AI-driven interactive voice response and phone automation.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
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Robotic agents struggled to engage. Now, expressive AI handles calls so naturally that users frequently mistake the bot for a human.
Standard models struggled with regional dialects. A custom audio layer over frozen Llama weights now powers voice AI for India.
Spikes across scattered channels bottlenecked support. Generative AI now fields voice and text instantly, with zero human aid.
Engineers manually correlated alerts across systems. AI agents now diagnose issues and suggest fixes, cutting recovery time by 35%.
Minor edits required days of crew coordination. Now, staff use avatars to modify dialogue and translate languages instantly.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.