Business Idea: We’re building a platform that trains and coaches sales development representatives in real-time during cold calls. Unlike standard call recording and coaching tools, our platform uses machine learning algorithms trained to detect tonality and conversational flow, analyzing pitch variation, pauses, filler words, talk-to-listen ratios, and objection handling. How it works • Training mode: SDRs practice calls and get feedback on tone, pace, question quality, and confidence before doing the actual call. • Live mode: During real calls, the system analyzes tonality and key conversational signals in real-time, prompting SDRs if they miss a discovery question, talk too much, or sound monotonous. • Company-specific training: The platform adapts to each company’s playbooks, ideal customer profiles, and objection-handling scripts. Differentiation: Most sales enablement tools (like Gong, Salesloft, Chorus) focus on call recording and post-call analytics. Our edge is real-time, tonality-aware coaching powered by ML, not just what was said, but how it was said. This makes training faster, coaching more precise, and SDR ramp time significantly shorter.

Most SDR teams struggle with cold call effectiveness. Reps are often: • Underprepared in tonality and conversation skills (they sound scripted, robotic, or unconfident). • Slow to ramp up because training is passive (videos, scripts, shadowing) instead of interactive and real-time. • Missing live opportunities on calls—forgetting to ask key questions, mishandling objections, or talking too much—without immediate correction. • Managers lack visibility into how calls are going beyond call outcomes, making coaching reactive instead of proactive. The result: wasted dials, longer ramp times, inconsistent messaging, and lost pipeline.