Florus.ai

Live · Self-improving GTM agent

RSI Agent

Marketing that improves itself.

A self-improving agent team for GTM. It runs campaigns, learns from results, and keeps what works — with you approving every change.

For founder teams, operators, and agencies running recurring GTM work.

Book a Demo

Demo-led · Custom deployment

RSI Agentcycle 07
Sample cycle
  1. RunLinkedIn series + 3 GEO fixes shipped
  2. MeasureCitations and replies pulled in
  3. Review2 defects: weak hook, unsourced claim
  4. CommitNew playbook + new pre-ship check
Cost per accepted asset · illustrative↘ compounding
01The RSI loop

Every cycle ends smarter.

It ships, measures, and keeps what worked — once you approve.

  1. 01RunShip campaigns, posts, fixes, and outreach.
  2. 02MeasurePull back citations, replies, and edits.
  3. 03ReviewScore results. Find the root cause.
  4. 04CommitTurn lessons into assets — with your approval.
  5. 05CompoundStart the next cycle from what was learned.
The RSI loop: run, measure, review, commit, compound — then the next cycle starts with what was learned.cycle n → n+1starts smarter01 Run02 Measure03 Review04 Commit05 Compound
02What compounds

What it keeps.

Only what pays for itself.

Memory

Market memory

ICP, voice, objections, and what has been tried.

Skills

Playbooks

Winning hooks and sequences, made reusable.

Harness

Quality checks

Repeated mistakes become pre-ship checks.

Routing

Routing policy

The right channel and model for each job.

Governed, not autopilot

Self-improving, never self-approving.

  • Risk-tiered review

    Brand, claims, and spend need a human.

  • Full ledger

    Every change is recorded with evidence.

  • Rollback

    Any asset can be retired when it stops paying.

03 · Our thesis

Recursive self-improvement will define the AI era. We point it at go-to-market.

01

Recurring work

The same jobs repeat, so lessons get reused.

02

Fast feedback

Results arrive in days, not quarters.

03

Reviewable output

Every asset is accepted or rejected — auditable.

The claim we measure

Same budget, more accepted work — every cycle.

What we instrument

  • Accepted assets per dollar
  • Repeat-defect rate
  • Asset reuse
  • Human override rate
Governance alpha hypothesisIllustrative only. Cost per accepted asset stays flat or rises for ungoverned agents and falls across cycles for a governed RSI loop.C1C2C3C4C5C6C7C8cost / accepted assetUngoverned agentsGoverned RSI loop
Illustrative hypothesis — not reported results.

Overview

  • Campaign execution
  • Outcome measurement
  • Governed learning ledger
  • Human-approved changes

What it does

Runs your recurring GTM work, measures what happened, and keeps what worked as memory, playbooks, and checks.

Built on the Nvidia DGX Spark champion agent team solution and deployed to your market and channels.

Why it is governed

Every change is proposed with evidence and routed by risk. Brand, claims, and spend changes need a human — and anything learned can be rolled back.

What does RSI mean?

Recursive self-improvement: the agent uses the results of its own work to do the next round better.

Does it change itself without approval?

No. It proposes changes; you approve the ones that matter. Every change is recorded and reversible.

Is the RSI Agent live?

Yes — available through a demo, with pricing based on your workflows.