Saurabh Chauhan

We essentially give the work to agents and we essentially put humans in management.

So that's where the order of magnitude games come from as far as both internal and external deployments look like when we're serving our clients.

Sure.

So 20X is a self-improving agent orchestrator.

It's open sourced on github.com slash peakflow slash 20X.

It's MIT licensed and the enterprise version is available on our website peakflow.co.

Essentially, the mental model is that 20X is the brain.

The models, AI models like Clart, GPT, Gemini, these are the underlying models, are essentially the hands.

And 20X decides what needs to happen, decomposes it into tasks, picks the right model for each, and then surfaces what needs human review.

And the three things that essentially separated from, you know, your run of the mill traditional automation would be, number one would be the heartbeats.

So essentially traditional automation waits to be triggered, but as 20X agents are checking proactively, just like a potential employee would be checking the work.

So...

For example, let's say three invoices are 45 days overdue and I'm just giving you an example of finance use case and or collection drafts are ready for approval.

This would be the sort of things that the agent would be proactively checking in the ERP and emails, whatever are the connected data sources and would be surfacing

tasks that require human in the loop or human intervention, but essentially an agent would be performing these checks.

And that's essentially one of its superpowers.

The second is schemes.

So schemes would be that every time an agent finishes a task, it updates its own playbook based on what it worked and confidence scores are tracked.

So over time, the runbook writes itself.

Most AI agents are confident in terms who