SHINTA.TECH
Book a 30-min Workflow Audit

USE-CASE LIBRARY

Real-World AI Automation Use Cases

Working systems, not slideware — each card shows the manual pain, the automation that removes it, and the pipeline underneath. Filter by your industry or by the capability you need.

SOLUTIONS FOR…
CAPABILITY…

THE CHALLENGE

"The school sends fifteen emails a week and somewhere in there is a trip that needs a consent form by Friday. I found out on Thursday night." Events, deadlines, and action items arrive buried in newsletters, and every family re-reads the same messages to keep two calendars in sync.

THE AI SOLUTION

Product Showcase: an in-house SaaS built solo to automate family-school communication — scans school emails, extracts events and action items, syncs to WhatsApp and calendars. GDPR-first, launching soon.

PIPELINE

SCHOOL EMAIL "Year 4 swimming starts Tue 9:00. Return the consent form by Friday." EXTRACTION AGENT EVENTS + ACTIONS EVENT Swim, Tue 9:00 ACTION Consent form DUE Friday CHILD Year 4 SYNC OUT WhatsApp digest Family calendar Reminders
SAMPLE DATA IS FICTIONAL.

INTERACTIVE DEMO

DEMO VIDEO — COMING

THE RESULT

In-house SaaS · launching soon No usage numbers here on purpose — Parent Inbox has no external users yet, and this site only publishes numbers you can verify.

TECH STACK

  • Python
  • FastAPI
  • Claude API
  • PostgreSQL
  • Next.js

THE CHALLENGE

"I need to send a follow-up to that lead — where are they? Which inbox, which spreadsheet, which notebook?" Leads arrive from networking events, referrals, and email enquiries, land in five different places, and follow-ups die because nobody can see who's waiting.

THE AI SOLUTION

A lightweight CRM dashboard with an extraction agent — raw enquiry emails and contact notes go in, clean lead records come out (name, company, intent, urgency), and a daily follow-up queue surfaces who to contact today with a drafted message ready to approve.

PIPELINE

RAW ENQUIRY "Hey, I need a Python dev for 3 months starting ASAP. Budget is £12k/month." EXTRACTION AGENT LEAD RECORD NAME James STATUS Hot lead INTENT Hiring TECH Python FOLLOW-UP QUEUE Due: today Draft ready One-tap approve
SAMPLE DATA IS FICTIONAL.

INTERACTIVE DEMO

PRE-COMPUTED EXAMPLES FROM THE DEMO SYSTEM — NO LIVE API CALL. SAMPLE DATA IS FICTIONAL.

RAW INPUT

EXTRACTED LEAD RECORD

EXAMPLE 1 / 3

THE RESULT

est. 2–4 hrs/week back Estimate, based on 20–30 minutes per day spent hunting leads across inboxes, spreadsheets and notebooks — not a measured client outcome.

TECH STACK

  • Next.js
  • Claude API
  • Unipile API
  • PostgreSQL

THE CHALLENGE

20–40 minutes per CV to rebuild into a client template. Every candidate submission means retyping the same experience into the same branded layout — evenings lost to formatting instead of placements.

THE AI SOLUTION

Parsing agent that ingests any CV (PDF/Word), extracts structure, and outputs a branded template with a consistency check pass.

PIPELINE

RAW CV (PDF/WORD) Any layout: tables, photos, mixed fonts, 2–6 pages, no two alike. PARSING AGENT STRUCTURED PROFILE NAME & ROLE EXPERIENCE [ ] SKILLS [ ] EDUCATION [ ] BRANDED OUTPUT Client template Consistency check DOCX / PDF out
SAMPLE DATA IS FICTIONAL.

INTERACTIVE DEMO

DEMO VIDEO — COMING

THE RESULT

20–40 min → ~2 min Measured on sample CVs run through the demo system — not a client outcome.

TECH STACK

  • Python
  • FastAPI
  • Claude API
PRODUCT SHOWCASE B2B / STARTUPS

Alumate

Coffee-chat network for Japanese students studying abroad. Built and operated solo, live today.

Your workflow could be the next card.

Book a 30-min Workflow Audit

Free, 30 minutes. You get a one-page automation plan either way.