Case Study

How FLYBICS Runs on AI Agents

A solo-founder AI consulting firm operating entirely on AI agents — lead generation, outreach, content marketing, customer support, development, QA, and operations reporting — for under $100/month. Here's the architecture, results, and lessons learned.

Published July 6, 20266 min read

Quick Answer

FLYBICS runs on six AI agents that automate lead research, outreach, content, support, development/QA, and ops reporting — all orchestrated in self-hosted n8n with the solo founder as the approval gate. The entire stack runs for under $30/month using free-tier LLM APIs and open-source tools.

The Challenge

FLYBICS is a solo-founder AI consulting and technology company. The challenge: operate like a full-service firm (sales, marketing, delivery, ops) with one person and a sub-$100/month budget.

Traditional approach: hire freelancers or agencies for each function ($5,000–15,000+/month). AI-powered approach: deploy AI agents for every function, with the founder as the director and approval gate.

The Solution: A 6-Agent Ecosystem

Agent 1Lead Research & Scoring

Trigger
Weekly batch from prospect lists / Apollo.io exports
Workflow
Scrapes company website → Gemini Flash summarizes company profile → AI agent scores leads (1–10) on automation pain signals, tech stack, size, decision-maker availability → Score ≥7 → enriched contact created in HubSpot with research notes
Result
30–50 researched, scored leads/week with zero manual research time.

Agent 2Personalized Outreach

Trigger
HubSpot contact enters "Enriched" stage with score ≥7
Workflow
Gemini drafts 3-touch sequence grounded in research notes (one specific observed fact, ≤120 words, soft CTA) → Founder approves/rejects in one click (n8n approval node) → Approved → sent via Instantly/Apollo sequences → Replies webhook back → Groq classifies (interested/question/not now/unsubscribe) → Drafts suggested response for founder
Result
Personalized sequences at scale; reply rates 3–5%; founder time per outreach: <5 min/day.

Agent 3Content Engine

Trigger
Weekly voice note or bullet list from founder
Workflow
Whisper → Gemini transcribes → Gemini Pro drafts SEO blog post in FLYBICS voice → Founder edits in Google Doc → Agent generates: 3 LinkedIn posts, 3 X posts, 1 carousel → scheduled via Buffer → Monthly: pulls Search Console data, proposes next month's topics
Result
4 pillar posts/month, 24 social posts, without a content team.

Agent 4Website Support & Intake

Trigger
Chatwoot widget conversation on flybics.com
Workflow
RAG query on Supabase vector store (service docs, FAQ, case studies) → Gemini answers with citations; offers Calendly link on buying intent → Low confidence → assigns to founder with full conversation summary → All conversations logged to HubSpot; qualified → auto-deal creation
Result
60%+ of conversations auto-resolved; 24/7 coverage without a support person.

Agent 5Dev & QA Pipeline

Trigger
GitHub PR
Workflow
Playwright suite runs; failures sent to n8n → LLM classifies each failure (bug vs flaky locator) → Locator fixes → auto-PR; real bugs → GitHub issue with label → Second LLM reviews PR diff for security/quality
Result
Deploy-to-client lead time <2 weeks per agent build.

Agent 6Ops Reporting

Trigger
Monday 07:00
Workflow
Pulls HubSpot pipeline, outreach stats, Buffer performance, Search Console, GitHub activity → Gemini writes one-page brief: wins, risks, three priorities → Delivered by email + Notion log
Result
Full business visibility in <5 minutes/week.

The Architecture

Layer 4: Delivery        CrewAI · LangGraph (client agent builds)
Layer 3: Functions       Apollo · HubSpot · Buffer · Chatwoot · GitHub · Calendly
Layer 2: Orchestration   n8n (self-hosted) — all agents live here
Layer 1: Intelligence    Gemini · Groq · Cerebras · OpenRouter (all free tiers)

The Stack

Every tool in the stack is either free tier or open-source. Total monthly cost: ~$30.

  • n8n (self-hosted)$0
  • Gemini AI Studio$0
  • Groq$0
  • Cerebras$0
  • OpenRouter$0
  • Claude Code Pro$20
  • HubSpot Free$0
  • Apollo.io Free$0
  • Buffer Free$0
  • Chatwoot (self-hosted)$0
  • Supabase Free$0
  • Total$30/month

Results (First 90 Days)

40Leads researched/week
4.2%Outreach reply rate
6Discovery calls/month
12Blog posts published
63%Support auto-resolution
2Paid engagements secured

Key Lessons Learned

  1. Human-in-the-loop is non-negotiable. The founder approval gate on outreach and content ensures quality. Agents draft; humans decide.
  2. Stack free tiers deliberately. Each provider has independent rate limits. Stacking 4 LLM providers multiplies free capacity without multiplying cost.
  3. Secondary domain for cold email. Never cold-email from your primary domain. Warm up 2–3 weeks before sending. Stay under 50/day/inbox.
  4. Context is everything. The outreach agent's quality depends entirely on the research notes it receives. Invest in the Lead Research Agent first.
  5. Measure everything. The Ops Reporting Agent makes invisible bottlenecks visible. If you can't measure it, you can't agent it.

Applicability to Your Business

This model works for any business where:

  • Knowledge work is a significant cost centre
  • Customer interactions are repetitive but require personalisation
  • You have data (or can gather it) to feed AI workflows
  • A human-in-the-loop approval model is acceptable

The same architecture that runs FLYBICS can be deployed for your organization — customized to your workflows, data sources, and compliance requirements. Typical build timeline: 1–2 weeks per agent.

Frequently Asked Questions

How much does it cost to run a business on AI agents?

FLYBICS operates its entire six-agent stack for about $30/month by combining free-tier LLM providers (Gemini, Groq, Cerebras, OpenRouter), self-hosted open-source tools (n8n, Chatwoot, Supabase), and free CRM/outreach tiers. The only paid line item is Claude Code Pro at $20/month.

What are the six AI agents FLYBICS uses?

1) Lead Research & Scoring, 2) Personalized Outreach, 3) Content Engine, 4) Website Support & Intake, 5) Dev & QA Pipeline, and 6) Ops Reporting. Each is triggered by a specific event and hands off to the founder for approval on high-stakes actions.

Can this AI agent model work for other businesses?

Yes. The model fits any business where knowledge work is a significant cost centre, customer interactions are repetitive but need personalisation, data is available to feed workflows, and a human-in-the-loop approval model is acceptable. Typical build timeline is 1–2 weeks per agent.

Is a human still involved when a business runs on AI agents?

Yes. Human-in-the-loop is non-negotiable at FLYBICS. Agents draft outreach, content, and code, but the founder approves or rejects high-stakes actions in one click. Agents propose; humans decide.

Build Your Own AI Workforce

Want to run on the same system?

We build the same AI agent ecosystems for our clients. Book a strategy call to map your highest-impact automation opportunities.

Book a Strategy Call