Building agents required weeks of manual logic and 3,000-token prompts. Now, GPT-4o manages the flow, letting teams go live in days.
A voice automation startup operating with a lean team of 11 engineers to replace legacy call center scripting with AI-native infrastructure.
Creating natural voice agents previously required chaining brittle instructions, manually managing context windows, and writing 3,000-token prompts...
“Because the models keep getting better, our platform keeps getting better. We’re not just scaling faster, we’re tackling more complex problems with a simpler stack.”
Platform for building and deploying conversational AI voice agents for phone calls.
AI research and deployment company developing generative models and tools.
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Rote tasks overwhelmed agents. AI now ingests CRM data and self-checks answers to resolve 93% of tickets autonomously.
Previous models wrote unusable partial code. Now, specialized agents with VM access build and deploy 5,000-line apps in two hours.
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.