AI Agent / Solo Company Build
Hand your repetitive work to AI employees
Custom AI Agent systems for solopreneurs, freelancers, and small teams. We delegate customer service, marketing, admin, research, writing, and follow-ups to agents — turning you into a 'one-person company with AI employees'.
Interested in AI Agent / Solo Company Build?
Drop your situation below. I'll reply within one business day with initial thoughts. Free, no hard sell.
- Solopreneur / creator / freelancer wanting to use AI leverage instead of hiring
- Founder short on hands, looking to fill admin / CS / marketing gaps with AI
- Using ChatGPT for chat only, not yet automating real workflows
- Want to build your own AI assistants / advisors
- Want agents that handle research, decks, writing, email, follow-ups
- 01/ Agent architecture design (single vs multi-agent orchestration)
- 02/ Tool integration (LLM API, knowledge base, vector DB)
- 03/ Automation glue (n8n / Make + agent triggers)
- 04/ Monitoring and cost controls (token usage, output quality)
- 05/ Documentation, walkthrough videos, 30-day post-launch consulting
- I combine engineering execution with business-process design — I know what should and shouldn't be automated
- I run my own consulting, site, and content distribution through AI agents — a working solo-AI-company in practice
- Beyond delivery, I teach you how to 'manage your AI employees': adjust prompts, evaluate output, iterate
LangChain, LangGraph, CrewAI, OpenAI Assistants API, Claude API, Anthropic Computer Use, n8n, Pinecone, Vercel
NT$15,000–150,000+
30-min discovery call → scope and pricing → phased delivery → launch handoff
6 Agent archetypes
Customer Service Agent — connects to LINE / web chat / email; auto-triage, FAQ handling, escalates to human when needed.
Marketing Agent — from one topic, fans out SEO articles, social posts, ad copy across multiple platforms.
Sales Agent — lead nurturing, pitch drafts, customer follow-up emails, automated CRM updates.
Research Agent — given a topic, crawls data, synthesizes, produces industry reports.
Internal Assistant Agent — meeting notes, calendar management, email triage, to-do sync.
Content Production Agent — one source (a long-form article, a podcast) → automatically produces shorts, threads, newsletter, social image cards.
Why this stack (LangGraph + n8n + vector DB)
LLM APIs are stateless — each conversation, the model doesn’t remember what happened before. Real Agents need:
- State management (LangGraph or OpenAI Assistants) — Agent remembers the goal and decision history across multi-step flows.
- Knowledge layer (Pinecone / vector DB) — your private docs (past projects, SOP, customer data) become real-time-queryable context.
- Action layer (n8n / Make) — once the Agent decides what to do, it actually sends the email, writes to Notion, pushes the LINE message.
- Monitoring layer — token usage, output quality, anomaly alerts.
Skip any layer and the Agent degenerates into “ChatGPT that talks a bit better”.
How I run my own AI company
The Luce Agentic engagement flow, content distribution, and customer follow-up all run on Agents — not a demo, the production system I rely on every day. So what I deliver isn’t a “working PoC” — it’s a “system I’d run myself”, complete with prompt-tuning guides and cost-control dashboard.
Browse other services or email me
If this isn't the right fit, see the rest of the catalog — or skip the form and send a message directly.