3 founding client spots remaining. Pilot pricing: $2,500 deployment + $500/mo.

Everyone Else Installs One Bot.
We Deploy 9-Agent Systems.

9 specialized agents coordinating autonomously, running your business ops while you focus on growth. Not a basic install — production-grade architecture.

Running in production — not a demo, not a tutorial

Tools Your Agents Can Use Right Now

Phantom Browser
Your agents browse Facebook, LinkedIn, and X without getting banned.
Undetectable browser automation that passes every stealth test. Real residential IPs, human-like mouse movements, unique fingerprints per profile. Runs 24/7 on a $6 server.
31/31 stealth tests passed
UGC Forge
Generate scroll-stopping UGC videos for any product in minutes.
8 AI models working in sequence — script, voice, avatar, lip sync, app mockups, animation, composition, and QA. Trained on 884 viral videos. Every video scored on 13 quality dimensions before delivery.
509M+ views in training corpus
🚀
Live Campaigns
Watch real agent-generated content performing across platforms.
Not mockups or demos — live campaigns with real engagement. Posts, threads, and video content created and distributed by our agent system. See what autonomous content production actually looks like.
100+ campaigns published

Pick Your Niche. See What 9 Agents Would Do For You.

One team went from $201K/mo to $1.25M/mo using AI agents to 29x their content output.
#AgentWhat It Does
1Agency ManagerClient intake, content calendars, deadline tracking
2Research AgentTopic research, competitor analysis, keyword/entity mapping
3Long-Form WriterBlog posts, whitepapers, case studies
4Short-Form WriterSocial posts, email copy, ad copy, captions
5SEO/GEO AgentOptimizes for Google AND AI search engines
6Editor/QA AgentQuality control, brand voice enforcement, fact-checking
7Repurposing AgentTurns 1 piece into 30 derivative assets across formats
8Distribution AgentSchedules and publishes across all platforms per client
9Analytics/ReportingTracks performance, generates client-facing dashboards
Your morning after deployment: 7 AM — Client content calendars auto-populated with trending topics. 12 articles drafted overnight across 3 clients. You review, approve 10, tweak 2. Distribution handles the rest. Your repurposing agent already turned yesterday's approved blog post into 28 social variants. You're running a content agency with a 5-minute morning review.
Why multi-agent: A single AI writer generates content. 9 agents run an entire agency — research, write, edit, optimize, repurpose, distribute, report. AI agencies hit 70-90% gross margins vs 40-60% traditional. The repurposing agent alone is the difference between $201K and $1.25M.
Inbound-led outbound converts 8x better than cold spray. AI agents generate 50-100 qualified leads/month on autopilot.
#AgentWhat It Does
1Campaign ManagerPlans outreach campaigns, sets ICP criteria, monitors pipeline
2Prospect HunterScrapes LinkedIn, Apollo, databases for ICP matches
3Enrichment AgentCompany data, tech stack, funding rounds, intent signals
4Signal MonitorWatches for engagement: comments, profile views, job changes
5Copywriter AgentPersonalized connection requests, DMs, email sequences
6LinkedIn OperatorExecutes safe LinkedIn actions with human-like patterns
7Email OperatorManages cold email sends, warmup, deliverability
8Response HandlerClassifies replies, routes or auto-responds
9CRM + PipelineLogs all activity, updates pipeline, generates weekly reports
Your morning after deployment: 7 AM — Overnight: Prospect Hunter found 12 new ICP matches. Enrichment Agent flagged 3 with recent funding rounds. Signal Monitor caught a VP who commented on your LinkedIn post at midnight. Copywriter drafted a personalized DM referencing their comment. You approve it. By 9 AM, your pipeline has 3 new warm conversations you didn't start manually.
Why multi-agent: Each agent stays in its lane. The LinkedIn agent never reasons about enrichment data. The copywriter never touches CRM logic. This prevents the "competence creep" that makes single-agent outreach sloppy and gets accounts flagged.
AI search visitors convert 4.4x better than Google organic. ChatGPT processes 2.5 billion prompts daily. Is your brand getting cited?
#AgentWhat It Does
1GEO OrchestratorReceives client brief, breaks into subtasks, coordinates
2Citation MonitorQueries ChatGPT, Perplexity, Gemini, Claude — tracks citations
3Technical SEOAudits llms.txt, robots.txt, schema markup, structured data
4Content CreatorWrites superlative lists, comparisons, FAQs that AI models cite
5Review MonitorTracks G2, Clutch, Capterra scores — AI trust signals
6PR OutreachIdentifies publication targets, drafts pitches, tracks coverage
7Competitor IntelMonitors competitor AI citations, identifies gaps
8Entity BuilderManages Wikipedia, Crunchbase, knowledge panel entries
9Visibility DashboardWeekly AI share-of-voice reports across all platforms
Your morning after deployment: 7 AM — Citation Monitor report: your brand was mentioned 14 times by ChatGPT this week, up from 8. Competitor Intel flagged your main competitor just got cited in a Perplexity "best tools" response — here's the content that triggered it. Content Creator already drafted a response piece. You're winning a game most businesses don't know exists yet.
Why multi-agent: GEO spans content, technical SEO, PR, reviews, entity management, and continuous monitoring across 4+ AI platforms simultaneously. No single agent can maintain quality across all disciplines. GEO agencies are billing $4,000-$50,000/mo and nobody in the OpenClaw space is touching it yet.
AI video costs $0.50-$30/minute vs $1,000-$50,000/minute traditional. 90-99% cost savings.
#AgentWhat It Does
1Production ManagerClient briefs, content calendars, production scheduling
2Research AgentAnalyzes client niche, competitor content, trending formats
3ScriptwriterGenerates scripts using proven framework templates
4Avatar ManagerManages character bibles, selects avatar per niche
5Video GeneratorInterfaces with HeyGen/Synthesia/fal.ai/Kling APIs
6Post-ProductionCaptions, music, transitions, thumbnails
7Distribution AgentPosts to YouTube, TikTok, Instagram, Facebook per client
8Analytics AgentTracks views, engagement, CTR — identifies winning formats
9Client CommsSends client updates, handles revision requests, manages approvals
Your morning after deployment: 7 AM — Production Manager shows 8 videos completed overnight across 4 clients. Scriptwriter used the "Most Interesting Man" framework for the HVAC client and "Before/After" for the roofing client. You review, approve 6, flag 2 for revision notes. Distribution queues them for optimal posting times. You just delivered a week of video content for 4 clients before breakfast.
Why multi-agent: Single-agent video generation = one video at a time, one style. 9 agents = parallel production across multiple clients, each with their own avatar, niche, and framework. This is how you scale from 1 client ($500/mo) to 20 clients ($10,000/mo) without proportional time increase.
A solo agent went from 18 deals/year to 52 deals/year (3x) by letting AI score, route, and nurture leads.
#AgentWhat It Does
1Brokerage ManagerOrchestrates all activities, routes leads, manages priorities
2Lead CaptureMonitors listing sites, captures inquiries, creates lead profiles
3Lead ScorerAnalyzes behavioral signals, scores leads 0-100
4Hot Lead AgentImmediately engages high-score leads via text, books showings
5Nurture Agent30-day drip sequences for medium-score leads
6Listing AgentGenerates property descriptions, virtual tours, social posts
7Market AnalystComp data, CMA reports, market trend tracking
8Transaction CoordinatorClosing checklists, deadline tracking, document collection
9Pipeline ReportConversion rates, agent performance, weekly dashboard
Your morning after deployment: 7 AM — Lead Scorer flagged 3 hot leads overnight (score 80+). Hot Lead Agent already texted them — 2 replied, 1 booked a showing for tomorrow. Nurture Agent sent personalized check-ins to 15 medium-score leads — 3 re-engaged. Listing Agent generated descriptions for 2 new listings. You're running a brokerage back office with zero staff.
Why multi-agent: Real estate is time-sensitive AND long-cycle simultaneously. Hot leads need instant response (minutes matter). Cold leads need 30-day nurture (consistency matters). A single agent can't be both fast-response AND patient-drip. Separate agents handle each timeline independently.
1% better pricing = 8-12% more operating profit. AI-generated descriptions: 300 in 2 hours vs 33 hours manually.
#AgentWhat It Does
1Store ManagerPrioritizes tasks, monitors overall store health
2Catalog AgentGenerates/optimizes product descriptions, structured data for AI search
3Pricing AgentMonitors competitors, adjusts prices based on demand and margin rules
4Inventory AgentTracks stock levels, triggers reorder alerts, forecasts demand
5Customer SupportHandles order inquiries, returns, FAQ — deflects 40-60% of tier-1 tickets
6Review ManagerMonitors reviews, drafts responses, flags product issues
7Marketing AgentEmail campaigns, social posts, ad copy from product data
8Analytics AgentConversion rates, AOV, cart abandonment — actionable insights
9GEO AgentOptimizes product data for AI search (37% of product discovery starts in ChatGPT)
Your morning after deployment: 7 AM — Pricing Agent adjusted 47 SKUs overnight based on competitor moves — projected +3% margin. Catalog Agent wrote descriptions for 12 new products. Customer Support handled 23 tickets while you slept. GEO Agent confirmed your top 5 products are now cited in ChatGPT shopping queries. Done before coffee.
Why multi-agent: E-commerce is a dozen different disciplines running in parallel — pricing, inventory, support, reviews, marketing, analytics. Each moves on a different cadence. A single agent switching between these tasks drops context and makes mistakes.
Klarna's AI handles 2/3 of customer chats — equivalent to 700 full-time agents — saving $40M/year.
#AgentWhat It Does
1Ops OrchestratorRoutes tasks, maintains priorities, escalates to humans
2Finance AgentExpense tracking, invoice processing, budget monitoring
3Customer SupportTier 1 resolution, FAQ handling, ticket routing
4HR AgentCandidate screening, onboarding workflows, leave management
5IT MonitorServer health, uptime monitoring, incident response
6Scheduling AgentMeeting coordination, resource allocation, calendar management
7Reporting AgentDaily/weekly dashboards compiled from all other agents
8Compliance AgentAudit trails, policy checks, data governance
9Communication AgentSlack/email notifications, inter-team communication
Your morning after deployment: 7 AM — Finance Agent flagged an invoice 23% over budget. IT Monitor caught a server spike at 3 AM, auto-scaled, resolved, logged it. Customer Support cleared 14 tickets overnight. HR Agent screened 6 applicants and surfaced 2 worth interviewing. You scan the dashboard in 5 minutes. Operations ran all night without you.
Why multi-agent: Operations span finance, HR, IT, support, scheduling, compliance — each a different domain with different urgency. A finance anomaly at 3 AM needs immediate flagging. An HR screening can wait until morning. Separate agents handle each domain on its own cadence.
One developer's agent checked a deployment, found root cause, updated configs, redeployed, and confirmed — all via voice while he walked his dog.
#AgentWhat It Does
1Tech LeadTriages issues, assigns to specialist agents, tracks resolution
2Bug DetectiveMonitors error logs (Sentry, Datadog), identifies patterns
3Root Cause AnalystDeep dives into stack traces, reproduces issues, identifies fix
4Code FixerWrites patches, creates PRs, runs tests
5Deployment AgentManages CI/CD pipelines, handles rollbacks, confirms deploys
6Infra MonitorServer health, scaling events, cost monitoring
7Security AgentDependency audits, vulnerability scanning, access review
8Documentation AgentUpdates READMEs, changelogs, runbooks after every incident
9Team ReporterIncident summaries, sprint reports, velocity tracking
Your morning after deployment: 7 AM — Bug Detective caught 3 errors at 2 AM. Root Cause Analyst identified a database connection pool issue. Code Fixer submitted a PR with the fix + tests. Deployment Agent pushed to staging, tests passed, promoted to production. Documentation Agent updated the runbook. You review the PR diff over coffee — it's already live.
Why multi-agent: Software operations are inherently multi-domain — monitoring, debugging, fixing, deploying, documenting. A single agent that monitors AND fixes AND deploys loses context between tasks and makes risky decisions. Separate agents with clear boundaries = safer, faster, more accountable.

This Isn't Theoretical. It's Running Right Now.

9 Agents Live in Production
40,525 Scraped Posts in Intelligence DB
16,265 Prospect Profiles Indexed
13 Active Campaigns Running

"Night 2 felt boring. That's how you know Night 1 worked."

Single-Agent Installs vs. Multi-Agent Architecture

What You Get Elsewhere

  • 1 agent on Telegram or WhatsApp
  • Generic skills from the registry
  • "Here's your bot, good luck"
  • No coordination between agents
  • No guardrails or trust system
  • One model for everything
  • No monitoring or health checks
  • Setup once, walk away

What You Get Here

  • 9 agents with distinct roles, models, and personalities
  • Custom SOUL.md + AGENTS.md per agent, built for your business
  • 6-stage deployment with validation at each stage
  • Hub-and-spoke routing — Chief of Staff delegates, agents collaborate
  • Trust level system — agents earn autonomy, nothing goes rogue
  • Model-per-agent pinning — flagship for reasoning, mid-tier for execution
  • Health monitoring, auto-restart, daily operational reports
  • $500/mo ongoing: model swaps, prompt recalibration, cost management

"The difference between installing a chatbot and deploying an operating system for your business."

The 9 Agent Archetypes

01

Router

Chief of Staff

Coordinates all agents, routes tasks, never does the work itself. Single point of contact.

02

Creator

Content Generator

Produces content matched to campaigns and frameworks. Your brand voice, at scale.

03

Sensor

Trend Engine

Monitors trends across platforms, matches signals to your campaigns in real time.

04

Distributor

Distribution

Posts to platforms at optimal times, manages rate limits and scheduling.

05

Observer

Overseer

Daily, weekly, and monthly reports. Campaign health monitoring. Only reports — never acts.

06

Operations

Operations

Morning briefs, evening check-ins, sprint tracking. Internal cadence and accountability.

07

Researcher

Research

Deep dives on demand. Competitor analysis, market intelligence, data gathering.

08

Funnel

Holding Funnel

Lead capture, email sequences, conversion tracking. Turns attention into revenue.

09

Memory

Human Replica

Learns your preferences over time. Guides other agents toward your style and standards.

Hub-and-spoke communication — no agent chaos
Trust level system — agents earn autonomy
Model-per-agent pinning — cost controlled
WhatsApp/Slack command interface — talk to your agents

What Your Day Looks Like with 9 Agents Running

7:00 AM

Morning brief hits your WhatsApp. Overnight metrics, trending topics matched to your campaigns, draft content waiting for approval.

7:05 AM

Approve 2 posts, delete 1. 5 minutes. Coffee time.

9:00 AM

Content posts automatically. Engagement monitored. DMs routed to your funnel agent for qualification.

2:00 PM

Trend alert — competitor post blowing up. You reply "do it." Fresh content live by 4 PM.

6:00 PM

Evening summary — what happened vs what was planned. Performance data. Tomorrow's queue already filling.

11:00 PM

You're asleep. Agents still running. Watching for signals, posting to international time zones, learning from today.

Sunday

Weekly deep analysis runs automatically. Trend patterns, content performance vs competitors, recommendations for next week.

Not Ready for a Full Deployment?
Start with the Architecture.

The 2-Night ClawBot Deployment Playbook — the exact sequence and architecture prompts we used to deploy 9 agents in 2 nights. Free PDF.

3 Founding Client Spots

Full Deployment at Pilot Pricing

We architect your agent team, spin up a dedicated server, deploy the full system, and hand you a running 9-agent operation with the keys.

$2,500 full deployment + $500/month to keep the system sharp

What You Get

  • Live architecture session — your business mapped to 9 agent roles
  • Custom SOUL.md, AGENTS.md, and config.yaml for every agent
  • Dedicated standalone server provisioned and configured
  • Full 6-stage deployment, tested at each stage
  • Health monitoring, auto-restart, daily backups
  • Server access credentials + handoff documentation
  • 2 weeks post-deployment support

What $500/Month Covers

  • Model swaps as the AI landscape shifts
  • Prompt recalibration when agent output drifts
  • Trust level graduation — agents earn more autonomy
  • Cost cap management as your usage grows
  • Health monitoring and system diagnostics
  • Async support with 24hr response
  • Server hosting ~$5-10/mo billed directly to you

In exchange, we document the build as a case study. Once the 3 spots fill, full pricing kicks in.

Book an Architecture Call →

No pitch on the call. We map your use case to the 9 archetypes and tell you honestly whether the pilot is a fit.

Frequently Asked

One agent is a chatbot. 9 specialized agents is an operating system. Your Router agent shouldn't also be writing content. Your Trend Engine shouldn't also be posting. Specialization means consistent quality and agents that actually improve over time. One agent doing everything leads to inconsistent output, personality drift, and no accountability.

You have a single agent answering questions. We build multi-agent systems where agents coordinate, delegate, and run autonomously. The gap between "installed" and "production system" is architecture — trust levels, model pinning, health monitoring, hub-and-spoke routing. That's what we deploy.

You still have a running system and we maintain it. The agents, prompts, and architecture are yours regardless of what happens to the platform. The founder moving to OpenAI actually makes the platform more stable, not less.

Yes — start with the free playbook. It gets you 60% there. The other 40% is what the deployment covers: delegation chains, trust levels, health monitoring, and the daily ops of keeping 9 agents aligned. The playbook gives you the plan. We handle the execution.

Matched per agent role. Flagship models on agents that reason or create. Mid-tier on agents that execute and report. Cost caps on everything. We pin models per agent so your brand voice stays consistent — no auto-routing that makes your coordinator sound like a different person every message.

Architecture in one session, deployment in another. 2 nights if you're hands-on, about a week if we handle everything. The 6-stage process means each stage must pass before the next — no shortcuts, no skipping ahead.

They install one agent on a Mac Mini and walk away. We deploy 9 coordinated agents with custom prompts, trust levels, model pinning, and ongoing maintenance. Different tier of service entirely. Think the difference between installing WordPress and building a SaaS platform.