Introducing Superagent

We just launched Superagent, and I'm excited to share what we've been building.

Hopefully you have seen by now that we just launched Airtable’s first standalone product, Superagent. I am the co-founder and CEO of Superagent, which is an evolution of the acquisition of DeepSky last fall. 

Most AI agents hit a wall when you ask them to tackle the kind of work that normally takes a team weeks to complete—comprehensive market research, competitive intelligence that tracks evolving landscapes, financial modeling that requires coordinating multiple analytical threads. They either get lost in their own complexity or produce surface-level summaries that miss what actually matters.

Superagent is different because it thinks like an organization, not like a single analyst grinding through a checklist. Instead of cramming everything into one context window and hoping for the best, it builds a knowledge graph around business intent. Every piece of research knows why it exists, what goal it serves, and how it connects to other insights. It breaks complex problems into parallel workstreams (like staffing a consulting project), actively seeks out contradictory evidence to avoid echoing consensus, and learns new methodologies on the fly when it encounters unfamiliar domains.

The result? Analyses that used to take weeks now complete in minutes, and the system gets smarter with every problem it solves because it builds institutional knowledge that compounds over time.

We built this because we kept seeing the same problem: businesses have genuinely hard questions that require deep research and synthesis, but the work is too expensive and time-consuming to do at the pace decisions actually need to be made. Superagent changes that equation entirely.