agent-coaching
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The Quality-Control Room That Learned to Listen
MaestroQA turned the dreary ritual of spot-checking support tickets into a searchable record of what customers actually say. Its next act is bigger, stranger, and now called Rippit.
Klaus Put Every Support Ticket on the Witness Stand
The cat mascot retired. Its sharpest idea did not: read every customer conversation, find the ones that matter, and turn quality assurance from spreadsheet archaeology into a working feedback loop.
CallMiner Spent 24 Years Teaching Companies to Listen. Now It Wants the Bots to Answer.
The Waltham software company built its business by finding patterns in calls that nobody had time to replay. Its next act is riskier: using those patterns to decide what humans should say - and what software should handle without them.
Intryc
Intryc is an AI-powered quality assurance platform for customer support teams. It evaluates up to 100% of support interactions in real time - human and AI-handled - using customizable scorecards, sampling rules and LLM-driven analysis, then turns those evaluations into coaching, training simulations and performance insights. Founded in 2023 by three ex-Revolut, Confluent, Amazon and Meta operators, Intryc went through Y Combinator's S24 batch and raised a $3.1M oversubscribed seed round in early 2025.
Ashish Nagar
Ashish Nagar is the Founder and CEO of Level AI, a Mountain View-based enterprise AI company that has raised $73.1 million to transform how contact centers operate. Armed with a B.Tech in Applied Physics from IIT Delhi, a Stanford MS, and a Stanford GSB MBA, Nagar cut his AI teeth building the Alexa Prize at Amazon — a project to make Alexa hold a 20-minute conversation on any topic, collaborating with researchers from MIT, CMU, Stanford, and Oxford. He founded Level AI in 2019 after recognizing that the same ambient AI breakthroughs powering voice assistants could be turned toward the unglamorous but massive world of customer service. The company's vertically integrated, CX-native large language model now analyzes 100% of customer conversations for enterprises like Affirm, Penske, and Carta, detecting seven distinct emotions, cutting call handling time by 10-25%, and onboarding agents 30-50% faster.