&Autonomous employees
We're a recursive self-improvement (RSI) lab for autonomous agent runtimes: AI employees that get better at getting better.
Trusted by 400+ Fastest Growing B2B teams
Meet Your First Employee
Rex, Your Autonomous GEO Employee
Rex monitors, optimizes, and publishes content 24/7 so your brand gets recommended by ChatGPT, Perplexity, Claude, and Google AI Overviews. Built on recursive self-improvement — not static automation.
Learn more about Rex →Get Cited by AI
- AI search visibility monitoring across all major LLMs
- Citation optimization for ChatGPT, Perplexity, Claude
- Brand mention tracking & sentiment analysis
- Content structured for AI retrieval & recommendation
Autonomous Content Engine
- GEO-optimized content generation with structured data
- Automated citations from authoritative sources
- CMS-wide content refresh on 30–60 day cycles
- Deep research engine for high-intent topics
Build Domain Authority for AI
- Track your AI domain authority score across LLMs
- Automated backlink outreach to top sources cited by AI
- Create lead magnets & organic content domains for 3rd-party authority
- Strategic link building to sources LLMs trust most
Compounds Over Time
- Optimizes its own experimentation strategy
- Learns from every publish & ranking signal
- Refines evaluation criteria autonomously
- Gets better at getting better
Why Rex Is Different
Most “AI employees” are stuck at Level 0
The search game changed. Your competitors are showing up in AI answers. You don't need another tool that gives you dashboards but no execution. You need an employee that actually does the work — and gets smarter doing it.
Execute Tasks
Most AI tools and "AI employees" run a static playbook. Write a blog post. Optimize a title tag. No learning. The agent on day 300 is identical to day 1.
Other AI employeesLearn from Outcomes
Track what worked. Adjust strategy based on results. Better over time — but only reactively, and only on the metrics you told it to watch.
Some emerging toolsImprove How They Learn
Rex optimizes its own experimentation strategy, evaluation criteria, and learning policies. It gets better at getting better — recursive self-improvement applied to your search visibility.
Rex by RelixirBreakthrough RSI Performance in Verticals
Rex outperforms frontier AI models and agent runtimes
Domain-specific agents vs. general-purpose agent runtimes across 1,200 production GEO workflows
Rex (Relixir)Rex (Relixir)Rex (Relixir)Domain-specific context orchestration eliminates 60-80% of wasted context window
How Rex Works
From Zero to Ranking in 3 Steps
No briefs. No agency retainers. No waiting. Connect Rex and watch your search visibility compound.
Learn more about Rex →Connect Your Tools
Link your CMS (WordPress, Webflow, Framer), analytics (GA4, GSC), GEO analytics, CRM (HubSpot), Slack, and more — Rex connects to your entire marketing stack with one click.
Rex Gets to Work
Rex starts writing, optimizing, and publishing GEO content — targeting AI citations and recommendations across ChatGPT, Perplexity, Claude, and Google AI Overviews. You approve or let Rex run autonomously.
Watch It Compound
Track AI citations, LLM recommendations, and inbound traffic in one dashboard. Rex continuously learns and improves, compounding your results every week.
Rex vs. the Alternatives
Not Another AI Tool
 Rex | GEO Agency | In-House Hire | GEO Tool | |
|---|---|---|---|---|
| Executes content autonomously | ✓ | — | — | — |
| Covers all AI search engines | ✓ | — | — | — |
| Learns and improves over time | ✓ | — | Slowly | — |
| Scales without headcount | ✓ | — | — | N/A |
| Built on recursive self-improvement | ✓ | — | — | — |
AI is an inflection point in the history of work. For the first time, agent runtimes give a single AI employee the ability to research, write, publish, analyze, and iterate — all autonomously, with persistent memory across sessions.[1]
General-purpose AI is becoming a commodity.[2] The real opportunity isn't building a smarter base model — it's building systems that accumulate domain-specific intelligence over time.
Most AI tools execute tasks. Some learn from outcomes. The next generation will improve how they learn — optimizing their own experimentation, evaluation, and strategy policies.[3]
We're proving this in GEO today. The architecture applies to every domain where you can measure outcomes.[4]
The companies that build recursive improvement systems for specific verticals will own those verticals.
[1] Wang et al., “A Survey on Large Language Model-based Autonomous Agents,” arXiv:2308.11432, 2023.
[2] Bommasani et al., “On the Opportunities and Risks of Foundation Models,” arXiv:2108.07258, 2021.
[3] Schmidhuber, J., “Gödel Machines: Fully Self-Referential Optimal Universal Self-Improvers,” Cognitive Technologies, Springer, 2007.
[4] Relixir Labs, “RSISEO-1: RSI Context Orchestration Benchmark,” Internal Technical Report, Feb 2026.
Design Philosophy
Built on Three
Non-Negotiables
The architectural decisions that separate compounding agents from static AI wrappers. These principles are structural, not aspirational.
Autonomous by Default
Our agents don't assist — they execute. Each Claw operates end-to-end within its domain, making decisions, taking actions, and optimizing outcomes without requiring human oversight.
Recursive Intelligence
Every agent runtime improves through recursive self-improvement. Performance compounds as agents optimize their own experimentation strategies, evaluation criteria, and learning policies — not just their outputs.
Native Integration
Claws connect directly to existing work infrastructure — CRMs, CMSs, analytics platforms, communication tools. No migration. No rip-and-replace. Intelligence that meets you where you already work.
Your competitors already hired Rex
See how Rex can get your brand recommended by ChatGPT, Perplexity, Claude, and Google AI Overviews — fully autonomously.