Saurabh Chauhan

The agent will pull signals from the available information for clients from CRM databases or agent databases.

It will automatically draft personalized sequences.

It would surface prospects that are relevant.

And then the judgment is then taken care of by the client.

actual human in the loop.

That's the same case for AI marketers that are the AI agents for content creation.

So our content lead would manage a marketing agent that runs weekly.

The agent would design the briefs, would design the draft, would do A-B testing based on subject lines, and would do the shipping.

But the human in the loop would essentially be our content head who would be reviewing all the work and the analytics that are derived from the AI marketer.

And same for our actual product that we deploy for lots of clients, which is our AI finance agent for back office automation.

This is what our customers have been running for.

Several years now, 100 plus enterprises, large, popular brands like Hitachi.

Their finance teams manage agents that do three-way matching, anomaly detection, vendor econ.

And essentially the outcomes are they're able to close their month-end

From reduce those times from 10 days all the way down to three days.

And I think the proof really is inside our own walls.

My CTO, Dimitri, literally shipped a full enterprise vendor decon product and four days, 10,000 lines of code, everything from document ingestion to data extraction, matching engine, full database schema, web app.

And he quite frankly didn't write any of the code.

He managed the team of five, six agents that he spun up who did write the code.

So that's essentially what 20S looks like when we love it, not just as a client-facing product, but also something that has created a massive impact in terms of our productivity internally.