Building a system of intelligent action
We built Aida to increase deal velocity and revenue capacity. Our ambition is to decouple revenue growth from headcount growth.
I led product from pre-launch through commercialization, working with design partners to identify repeatable workflows and turn those insights into the product.
Where we invested
We invested in the context graph from the start. Customer conversations, commitments and deal history needed to stay connected so Aida could understand where attention was needed and help across workflows.
Our initial discovery and design partnerships focused on the rep’s work. Removing administration could help the seller while improving the information the rest of the organization depended on. We then expanded how that context supported teams and execution.
Its system of intelligent action gives revenue teams AI agents that understand their business, execute company playbooks, and learn from customer interactions and outcomes. That learning improves how agents work across people and accounts, so lessons from one deal can inform decisions and actions across the team.
Help the rep
Understand and advance my deals without reconstructing context or losing selling time to administration.
Capture and recaps, extraction and CRM writeback, Ask and Assist, research, preparation, drafting and follow-through.
Align the team
Apply our standards consistently and identify where intervention will improve outcomes.
Mappings and playbooks, framework scoring, coaching and scoped rubrics, win/loss analysis, risk monitoring and relevant personalization.
Get work done
Delegate recurring work, arrive ready to act, and anticipate what happens next.
Scheduled workflows, recurring outputs, bulk activities, email drafting, agentic execution within supported boundaries and deal forecasting.