AIdeazz AI Lab · live in production

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AIdeazz AI Lab
Operations & Marketing Engine

This is not a demo. Eleven AI co-founder agents plus a marketing engine run 24/7: your website finds you, content publishes daily, leads land in CRM, and Atlas measures whether campaigns actually moved the needle. Below: plain-language status for business owners, then technical depth for engineers who need proof.

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AI Search Visibility • WhatsApp Agents • AI Automation

Author
Elena Revicheva
Updated
July 22, 2026
Status
Live in production

For engineers: authoritative product details—canonical agent list, GitHub repos, Oracle VM deploy paths, systemd/PM2 names, health checks, local Windows clones, and resilience postmortems—are maintained in ORACLE_ALL_PRODUCTS_RESILIENCE.md (engineering appendix). This public page stays founder-readable: no IPs, ports, or secrets.

What a business owner should take away
Start here

What AIdeazz AI Lab is — right now

Your production AI co-founder fleet plus a marketing engine that connects discovery → content → leads → measurement. Not a prototype.

PieceRoleWhere to see it
Public facePortfolio, blog, inquiry formaideazz.xyz/portfolio
AI Visibility AuditFree live API + widget — score any site 0–100 on GEO · AEO · tech SEO (ChatGPT / Perplexity / Claude / Gemini readiness)aideazz.xyz/api
Tech hubCRM, blog, outreach, performance trackingCTO AIPA Telegram
Marketing radarWeekly ad-market intelligence on the lab’s seven sellable services — open windows arrive as ready-to-run sales briefs, and CRM outcomes feed back so the radar learns what convertsAtlas live radar
CRM spineAll agents feed one HubSpot pipelineHubSpot Sales Pipeline
Measure layerWebsite sessions, form leads, deals by campaignAtlas concept cards (performance block)
Sibling productsEspaLuz tutoring, job hunter, social bots, creative AI, daily briefingPortfolio

Marketing engine flow (closed loop, July 2026): SEO & discoverability → daily blog → inquiry form with tracking → HubSpot → lead triage → outreach → Atlas detects a market window for a service we sell → sales brief lands in Telegram → outreach goes out → CRM outcome (sent / replied / won) flows back into Atlas → next week’s briefs are smarter

StatusReality (July 21, 2026)
LoadedDiscovery, content, CRM ingest, triage, Atlas radar on the lab’s seven service lanes, performance bridge, GA4 sync, WhatsApp click tracking, Telegram sales briefs + CRM outcomes feedback (Jul 21)
PartialConversion — the loop’s first honest read: outreach reply rate ≈ 4% on the visibility-audit lane (24 sends → 1 reply). The engine now measures this per service; beating it is the current game.
NextShowcase package for clients; automated weekly blog from each Atlas snapshot; ads API read
PhaseMarketing roadmapStatus
1Foundation — SEO, analytics, trust signalsLoaded
2Content — daily Dev.to blogLoaded
3Attribution + Atlas measureCRM outcomes loop live (Jul 21)
4Outbound (WhatsApp-first prospect play + Atlas briefs)Live · measured per service
5Lead triageOperational
6Client showcase packagePriority
How to verify (no terminal required):
  • Open Atlas — the snapshot refreshes every Monday ~9:15 AM Panama and should show the most recent Monday’s date.
  • Open the angle API — live market angle for a service lane, with real CRM outcomes, as JSON. This is the same intelligence the sales briefs use.
  • Visit aideazz.xyz/blog — new articles publish on a daily cadence, including posts written from Atlas’s own weekly snapshot.
  • Submit the inquiry form on aideazz.xyz/portfolio — you receive a confirmation email when it works (or use the form right on this page, below the go-to-market pipeline).
  • Engineers: full runbook in Marketing Engine roadmap on GitHub.
0
Tracked capabilities · 10 live · 1 roadmap (AILA)
0
Infrastructure layers · Oracle · AWS · static edge
0
Automated health cadence
0
Repos powering live products · all on one server
14
Manual steps in milestone → social pipeline
Section 01

Products & agents

Each row is a shipping capability—what customers or partners touch—with how it runs underneath (Linux services, process supervisor, or serverless). Naming matches the internal resilience matrix without exposing infrastructure coordinates.

GEO + SEO infrastructure · aideazz.xyz · AI-crawler signals · bilingual blog · lead capture → Oracle CRM pipeline (HubSpot) + prospecting from hiring boards & product launches X growth automation (stream listening + engagement + alerts) Morning briefing audio via AWS Lambda + secure CTO data bridge Executive rhythm: Trello digests to Telegram Live web data layer: Bright Data Web Unlocker · SERP · Scraping Browser + autonomous Claude research agent (/research_company · /research_employer · /research_competitor in Telegram) Multi-provider LLM failover, fleet-wide: every agent falls Claude → Groq (free Llama) at minimum—including all three EspaLuz bots—with Grok (xAI), OpenAI, and Gemini as extra tiers in higher-volume products (Atlas Shifted: Claude → Groq → OpenAI → Grok). The content engine survives any single provider outage.
Operational invariant: exactly one deployed checkout per GitHub repository—prevents version drift, duplicate secrets, and “which folder is live?” incidents. Pairs like CTO + creative co-founder deliberately share a codebase but run as distinct personalities/interfaces.
# Agent Role (business + ops) Runtime Status
01 EspaLuz WhatsApp Channel: Spanish tutoring on WhatsApp—conversation, drills, corrections.
Runs as a managed Linux service (espaluz-whatsapp) with automated health checks.
systemd ● Live
02 EspaLuz Telegram Channel: Same tutoring product on Telegram.
Two-layer memory: retrieval + pgvector RAG (espaluz_rag.py). Service espaluz-familybot.
systemd ● Live
03 EspaLuz Influencer Brand: Instagram publishing on a disciplined schedule; can spotlight real shipping milestones in consumer-friendly copy.
Groq captions + Make.com media handoff. Unit espaluz-influencer.
systemd ● Live
04 Algom Alpha (@reviceva) Growth: Always-on X presence (education + narrative); folds major releases into the timeline without sounding like raw developer logs.
Stream sampling, engagement runner, and account-activity hooks coordinated with the CTO bot for alerts / follow-back. PM2 workers include dragontrade-main and satellite processes.
PM2 ● Live
05 VibeJob Hunter Product: Autonomous job hunt pipeline—evaluation harness, routing, ATS integrations.
Shares codebase with the marketing co-founder agent. Worker vibejobhunter.
systemd ● Live
06 AI Marketing Co-Founder (CMO AIPA) Revenue narrative: LinkedIn cadence, long-form syndication, CRM hygiene—turns engineering momentum into market-facing proof.
Claude + connectors for social; Hunter.io enrichment → HubSpot. Paired FastAPI bridge vibejobhunter-web exposes an internal health route.
systemd ● Live
07 OpenClaw Vibejob Shortlist UX: Curated job shortlists delivered inside Telegram.
Standalone gateway service openclaw-gateway; probed via private health URL on the app host.
systemd ● Live
08 Tech Co-Founder (CTO AIPA) Control tower: Watches repositories, scores riskier changes, broadcasts milestones to marketing, runs outreach/board workflows.
Express orchestrator under PM2 (cto-aipa), Oracle Autonomous DB via wallet-based TLS—credentials never live in this HTML.
PM2 ● Live
08.1 Sprint Briefing (Sprinter) Founder ritual: Daily audio briefing synthesized from tasks, notes, and captures.
AWS Lambda on a schedule; pulls context through the CTO service over HTTPS with shared-secret auth—no database wallet inside Lambda.
Lambda ● Live
09 Creative Co-Founder (Atuona CCF) Creative partner: Separate bot persona + public studio site—same reliability envelope as the CTO stack.
Single PM2 orchestrator binary; site ships via static edge hosting.
PM2 ● Live
10 Atlas Shifted (Marketing Strategist) Marketing intelligence: Watches the public ad market daily (9 AM Panama), scores which angle is opening, exports test campaigns, and—since July 2026—pulls real Google Analytics sessions back into a performance ledger so you can see if a test moved traffic.
Detect → create → measure loop. Public ad-transparency data only for detection; GA4 for outcomes. Live at atlas.html.
PM2 ● Live
11 AILA Roadmap: Long-horizon personal orchestration—documented architecture, not yet a standalone production process.
Interim coordination fields live in Oracle until AILA ships.
In design
Section 02

Reliability & uptime practice

For founders: scheduled probes ask each product whether it still responds. For engineers: one bash driver on the primary Oracle VM runs roughly every five minutes; keep-alive traffic avoids idle reclamation; systemd caps restart storms.

No noisy herd restarts: failed probes recycle only the affected unit. Concrete URLs and scripts remain in the private appendix—not pasted here.
Model retirements are config, not rewrites: providers retire hosted models every few months (Groq drops Llama 3.3 for its dev tier in Aug 2026). Every agent resolves its model id through one fleet-wide switch, so a cutover is a one-line .env change — tested against a golden-set eval before flipping, and instantly reversible. The switch shipped fleet-wide in July 2026, weeks ahead of the deadline. For founders: the AI vendor treadmill is priced into the architecture, not paid for in rebuild weeks.
Agent
Health check method
Recovery action
CTO AIPA + Atuona
Orchestrator HTTP OK via localhost probe
pm2 restart cto-aipa
EspaLuz WhatsApp
Tutoring webhook answers OK from localhost
systemctl restart espaluz-whatsapp
VibeJob Hunter + CMO
Marketing bridge health endpoint OK internally
systemctl restart vibejobhunter-web vibejobhunter
OpenClaw Shortlist
HTTP GET gateway loopback → 200
systemctl restart openclaw-gateway
Sprint Briefing
CloudWatch + EventBridge schedule
Lambda retries / DLQ policy
PM2 stacks (e.g. Algom)
cron HTTP + pm2 jlist status online
pm2 restart <app>
All systemd agents
Process liveness via systemctl
systemd restart policy
Section 03

Go-to-market automation

When engineering ships something worth talking about, the stack fans it out across LinkedIn, blogs, X, and Instagram—without a human retyping the same story five times. And when a lead comes back in, the same stack answers first.

Quality gate: only commits tagged feat:, launch:, or release: notify the marketing agent. Housekeeping commits (fix:, docs:, chore:, …) stay invisible to customers.
1
GitHub Webhook

Commit detected → CTO AIPA

Push events hit the secured webhook. Groq/Claude review diffs, classify milestones, enqueue pending updates for downstream marketers.

2
LinkedIn · 20:00 Panama

CMO generates + posts

Claude Sonnet copy → Make.com delivery. Zero manual paste.

3
Daily blog · aideazz.xyz/blog + dev.to

Bilingual blog publish (EN/ES)

The daily blog publisher ships articles to aideazz.xyz/blog with dev.to crosspost (“Also on Dev.to”). Sliding-window mutex, title dedup, and always-notify Telegram guard against silent double publishes.

4
X · Every 5th post slot

Algom Alpha tweet

x-tech-updater.js merges milestones in plain language (Haiku / Groq), guarded against duplicate queue states.

5
Instagram · Even days 18:00 Panama

EspaLuz Influencer

Milestone-aware caption + Make.com media pipeline; falls back to standard queue when nothing pending.

6
Inbound · HubSpot → Claude → Telegram

Lead Concierge — form to sent reply in minutes

Portfolio inquiries become HubSpot contacts in seconds (server-side push, no cron wait). Make.com wakes Claude to draft a personalized reply—right language, right proof links, concrete first-engagement offer—delivered to Telegram with Send / Edit / Skip buttons. One tap emails the lead from the company domain and logs the sent text to the contact’s CRM timeline. Full audit trail, human approval on every send, response time cut from days to minutes.

Don’t take the diagram’s word for it — this form IS the pipeline. Submit it and you become a UTM-attributed HubSpot contact within seconds, Claude drafts a reply with full context of this operation, and it reaches my Telegram for one-tap approval. You’ll hear back fast — that’s the whole point of step 6.
Protected by reCAPTCHA Enterprise · Attributed as utm_source=sop-ai-ops so you can ask me later exactly how your own submission moved through the CRM.
Section 04

Release discipline

Board-friendly translation: we ship like a product company—predictable processes, isolated secrets, verifiable rollouts—even though agents move faster than most teams.

Rule · 01

One live checkout per codebase

Eliminates “which folder is prod?” debates; paired bots share code intentionally but never duplicate repos.

Rule · 02

Green build, then swap

Pull latest → compile/tests succeed → only then restart supervised processes. Broken artifacts never replace what customers already rely on.

Rule · 03

Secrets isolation

Each bot owns its environment file; crypto wallets never touch GitHub; TypeScript strict mode catches sloppy typings before prod.

Rule · 04

Crash-proof process registry

Every agent process is registered to auto-start on server boot and auto-restart on failure—no manual babysitting after a power cycle or kernel update.

Rule · 05

No silent failures

Crash handlers log before exit so supervisors show why something died; watchdog cadence targets ~5 minute detection.

Rule · 06

Verify after deploy

Health signal green, database connectivity logs clean, one real Telegram interaction—all pass before the incident is closed.

Section 05

Incident response template

For stakeholders: regressions are handled like financial reconciliations—symptoms, compounded causes, fix, proof—so the same automation trap rarely strikes twice.

HubSpot duplicate posting loop

May 10, 2026 — same milestone tweet emitted twice ~6 minutes apart

Symptom
Pending HubSpot milestones resurfaced every x-tech-updater.js cycle.
Root causes
Triple mismatch: legacy posted vs filter on posted_x; mark endpoint keyed on timestamp while older rows used received_at; backlog needed posted_x backfill.
Fix applied
GET excludes either flag; mark endpoint tries timestamp → received_at → title; JS client sends title for fallback matching.
Verified by
API snapshot {"ok": true, "pending": [], "total": 0, "held": true} + two full automation cycles without duplication.
Resolution
≈2 hours from detection → patched APIs → verified on live automation cycles. Full narrative retained in the engineering appendix linked below.

The engagement loop that never ran

May 25, 2026 — config said “32 engagements/day”; logs said zero cycles had ever completed

Symptom
Asked the logs to prove a claimed engagement rate. Startup banner found 4,357 times; cycle-completed action line found zero times. The behavior never happened, no matter what the config said.
Root causes
Three layers deep: the first engagement run was scheduled 5 minutes after startup; the process was being restarted every 5 minutes by an external cron; and that cron was a health check whose grep never matched PM2’s box-drawing table output—so it judged a healthy process dead, forever.
Fix applied
Health check rewritten to read structured state: pm2 jlist | jq on the process status field instead of grepping rendered text. Process stayed up; the first engagement cycle in the bot’s history fired the same day, with real replies and follows verified from logs.
Rule earned
Verify from logs, not config. Never claim agent behavior without grepping for the ACTION line (not the setup line). The fix is now a standing operating rule across the fleet.
SOP update rule: materially production-facing incidents earn the same structured write-up internally—so institutional memory compounds instead of resetting.
Section 06

Stack reference

Boring reliability primitives where uptime matters; sharp AI + CRM + social APIs where differentiation matters.

Process Mgmt
PM2 · systemd · AWS Lambda + EventBridge
Databases
Oracle Autonomous DB (enterprise-grade encrypted connection, multi-table estate) · PostgreSQL + pgvector (semantic memory for tutoring agents)
CRM & Outreach
HubSpot CRM v3 + v4 associations · Hunter.io · Resend
Social
X API v2 (Account Activity, filtered stream, engagement worker) · Make.com · Telegram Bot API
AI / LLMs
Claude Sonnet / Haiku · Groq (open-model inference — model id resolved via one fleet-wide switch, so provider deprecations are a one-line config change) · Grok (xAI, tier-3 failover) · OpenAI (gpt-4o-mini + text-embedding-3-small + TTS / Whisper) with retry + provider-fallback chain · Bright Data (public ad-transparency capture) · Runway (Seedance 2.0 / Kling 3.0) + Flux 1.1 Pro for Atlas creative · LangChain · LangGraph
Lead Gen
HN Algolia · GitHub REST · Product Hunt GraphQL · Bright Data (SERP API + Web Unlocker + Scraping Browser — replaced paid SerpAPI) — ~150–250 net-new companies/month after filtering
Hosting / CDN
OCI Ubuntu VM (VM.Standard.E5.Flex, 12 GB) · AWS Lambda · 4everland IPFS frontends · Cloudflare DNS
Monitoring
Cron health driver · PM2 logs · CloudWatch · curl probes · OCI keep-alive
Content & SEO
Bilingual daily blog · dev.to crosspost · GA4 + Atlas campaign measure (Jul 2026) · Google Search Console · GEO pack · lead capture → Oracle → HubSpot
Project Mgmt
Trello API (daily + weekly Telegram briefings) · GitHub webhooks across the fleet
Section 07

Questions people actually ask

The five questions that come up most, answered plainly — and marked up so AI answer engines can lift them directly.

What is the AIdeazz AI Lab?

A production fleet of eleven AI co-founder agents plus a marketing engine, running 24/7 on a single Oracle VM at zero monthly infrastructure cost. It publishes content daily, captures leads into a CRM, and measures whether campaigns moved the needle rather than reporting vanity metrics.

How does AIdeazz keep AI agents from dying silently?

Every product declares a health check, a restart command and a process name in one resilience config. A watchdog polls those checks and restarts a dead process, and failures surface in Telegram rather than waiting to be noticed. Silent death was the original failure mode, so a service that stops answering is treated as an incident, not a gap in the graph.

Does the marketing engine generate leads, or only traffic?

Inbound inquiries post from the website into Oracle and HubSpot instantly, then a Make scenario drafts a reply that is approved from Telegram before it sends. More than 900 deals and 500 contacts exist in the CRM. Attribution is instrumented end to end with UTM tags, though campaign volume is still low.

How is content optimized for AI search, not just Google?

A 34-check audit engine scores every page for AI crawler access, structured data, answer-readiness and technical foundation. robots.txt explicitly allows 28 AI crawlers including GPTBot, ClaudeBot and PerplexityBot, and llms.txt plus a geo-manifest give answer engines a content map. A weekly citation probe then asks Google AI Overviews, Gemini and OpenAI search whether AIdeazz was actually cited.

Who is this page for?

Business owners who want a plain-language view of what is live, and engineers who want proof. The engineering appendix with repositories, deploy paths, health checks and postmortems lives on GitHub, so this page stays readable and contains no IP addresses, ports or secrets.