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🇯🇵 日本のスタートアップの皆さんへ
AI機能をスピーディーに形にします。
・RAG／社内ナレッジ検索
・既存プロダクトへのLLM組み込み（OpenAI / Claude / Gemini）
・AIエージェント・業務自動化（Slack / Jira / メール連携）
・MVP開発（Next.js / Node.js / Python）
タスクごとに時間でお見積もりし、初回デモは約3営業日。
「このAI機能、どれくらいで作れる？」という段階でも、タスク分解と見積もりを無料でお送りします。
日本語でお気軽にメッセージください。
🌏 For startups in Japan (and beyond)
We build AI features fast: RAG, LLM integrations, AI agents and MVPs.
Every task is estimated in hours up front, and you get a working demo in about 3 business days.
Send me your idea and I'll reply with a free task-and-hours breakdown. Japanese or English is fine.
The three day demo promise stands out; packing a RAG setup and LLM hooks into that window must involve tight task slicing.
Ha, you guessed it! 😍
We break every request into small tasks first. Our engineers handle the design and review, while an AI agent writes and tests the code in parallel, even overnight. The first demo usually covers just one core flow working end to end, like: upload docs → ask...
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Top-notch design.
Building AI agents is easy. Building one you can trust with a real business workflow is harder.
I built a Freelance Admin Agent to explore that problem using Strands Agents SDK and Claude Sonnet 4.5 on Amazon Bedrock.
The working MVP takes manually provided client emails and turns them into a structured payment workflow:
→ Classifies invoice and payment emails
→ Extracts client, invoice, amount, currency, dates and contextual details using structured output
→ Stores and matches records in SQLite
→ Uses deterministic logic to identify full/short and on-time/late payments
→ Uses a second agent to draft a contextual follow-up only when needed
→ Keeps the final decision with the human through Approve / Edit / Reject
One of the most valuable parts wasn't adding another AI feature. It was finding a real reliability issue during testing: reprocessing the same email could duplicate records and inflate payment totals.
I reproduced it through repeat testing, traced the database behavior, and fixed it.
That reinforced something I'm increasingly applying to my AI engineering work:
A useful AI product isn't just an LLM call. It needs clear boundaries between AI reasoning, structured data, deterministic business logic, persistence, testing, and human control.
The next iteration will focus on stronger production safeguards, including source-grounded financial extraction, precise currency handling, stricter trust boundaries for untrusted input, and eventually live inbox integrations.
I'm interested in building more systems like this for startups and teams with repetitive workflows that can genuinely benefit from AI agents and automation.
Stack: Python · Strands Agents SDK · Amazon Bedrock · Claude Sonnet 4.5 · Pydantic · SQLite · Streamlit
turning client emails into admin tasks is such a real freelancer pain, nice build 🔥
Challenge Submission – Lovable Challenge
Business Name: Clemxy Dentistory Genius
Business Type: Premium Dental Clinic
Location: Banana Island, Lagos, Nigeria
Business Quirks:
Solo dentist managing a busy practice
Limited administrative support
High volume of appointment inquiries
Frequent patient no-shows
Significant time spent on scheduling, reminders, and follow-ups
Problem Solved (One Line):
I built an AI-powered appointment concierge that automatically converts patient inquiries into confirmed bookings while eliminating the clinic's manual scheduling, reminder, and follow-up workload.
Project Built With Lovable:
https://pixel-perfect-display-2164.lovable.app/
Demo Video:
Attached – Patient journey walkthrough from inquiry to confirmed booking.
Build Process Video:
Attached – Behind-the-scenes walkthrough showing how the solution was designed and built in Lovable.
LinkedIn Post:
https://lnkd.in/p/etn23YDu
Solution Highlights
AI Receptionist
Real-time appointment booking
Automated confirmations
WhatsApp, SMS, and Email reminders
Self-service rescheduling
Lead recovery automation
Clinic performance dashboard
No-show reduction workflow
Built entirely in Lovable to demonstrate how AI can automate appointment-based businesses and help owners spend less time on administration and more time serving customers.
@Lovable #lovablechallenge #AI #Automation #HealthcareTech #DentalTech #NoCode #VibeCoding #BusinessAutomation #BuildInPublic #ClemxyTech