4 papers
Augur: A Synthetic Decision Lab for Rehearsing Reactions to Product and Policy Changes
Rahul Khedar, Mayank Malhotra, Avinash Karn
Before a product or policy change ships, the question that matters is how people will react to it. Augur rehearses that reaction offline: it builds a typed knowledge graph from the…
A Three-Tier Persona Vector for Controllable User Simulation in Agentic Evaluation
Rahul Khedar, Eshita, Sneha Teja Sree Reddy Thondapu +6
Evaluating tool-augmented LLM agents requires diverse, realistic user inputs yet most evaluation frameworks use flat role descriptions ("you are an angry customer") that produce ne…
Rehearsed Multi-Agent Live Product Demonstrations with Real-Time Voice Question Answering
Rahul Khedar, Mayank Malhotra, Avinash Karn +2
Live product demonstrations are a recurring, high-cost activity in software organizations: a human presenter must select features, dispatch the corresponding interactions on a runn…
State-Grounded Multi-Agent Synthetic Data Generation for Tool-Augmented LLMs
Rahul Khedar, Eshita, Sneha Teja Sree Reddy Thondapu +10
Training tool-augmented LLM agents requires large corpora of multi-turn, tool-grounded conversational data that is expensive to annotate, privacy-constrained in production settings…