Plan AI Logo

Repetitive work
gone in 14 days.

Save 3-6 minutes per task with AI automation. Proven with metrics.

14일
PoC Completion
From consultation to working system. Not just a report.
3-6분
Saved Per Task
Average from real clients. 100 tasks = 500 min saved/day.
0건
Failed Projects
All projects met targets. Full refund if we don't.

Systems, Not Reports

Get a working automation system in 14 days. Complete with API integration, data processing, and error handling.

What you actually get

Web dashboard or Slack/Teams bot (tailored to your workflow)
Python/Node.js automation scripts + scheduler
Integration with existing tools (API or Webhook)
Error alerts & logging system
Tested working system (code + deployment)
Before/after metrics (time, accuracy, cost)
Deployment guide + operations manual (troubleshooting, rollback)

Performance Guarantee

If pre-agreed targets (processing time, accuracy, cost savings) aren't met, we rework or refund in full.

How targets are set

1.Sample 20-30 current tasks → measure avg time/accuracy
2.Agree on targets: X% faster, Y% accuracy (e.g., 5min→30sec, 95% accuracy)
3.Day 13: Re-measure with 20-50 real cases → verify targets met
Free rework if targets missed

If day-14 validation fails, 7 more days for free

Full refund if rework fails

100% refund if still below targets after rework

1-month free tech support

Slack/email within 24h, critical issues within 4h

Proven Cases

Real Results

전자상거래A사 · 마케팅팀

유료 퍼포먼스 리포트 자동 생성 & 예산 라우팅

Problem

채널별 성과 집계에 많은 수작업이 필요하고, 예산 조정이 늦게 이루어짐.

⚙️Solution

광고 API 연동 → 데이터 정제 → LLM 리포트 생성 → 임계치 기반 예산 라우팅.

Impact
CPA 18%↓
리포트 제작 6h→15m
의사결정 리드타임 3일→6시간
Detailed Metrics
정확도 98.9%자동화 커버리지 82%알림 응답률 94%
SaaSB사 · 영업본부

리드 정제·스코어링 & 자동 할당

Problem

중복/저품질 리드로 파이프라인 효율이 낮고, 응답 지연이 잦음.

⚙️Solution

정규화·디듑·스코어링 모델 → 라우팅 규칙 → SLA 경보.

Impact
MQL→SQL 전환 +11pt
응답 12분→90초
중복리드 0.6%
Detailed Metrics
SLA 99.6%핸드오프로스 41%↓리드 소스 정확도 +9pt
에듀테크C사 · 고객센터

문의 요약·우선순위 분류 & 라우팅

Problem

장문 문의를 사람이 모두 읽고 분류해 시간이 많이 소요됨.

⚙️Solution

요약·분류 에이전트 → 지식베이스 참조 → 예외 라우팅.

Impact
건당 처리 4분↓
SLA 99.7%
오류율 0.8%
Detailed Metrics
오탐율 1.1%자동응답 만족도 4.4/5백로그 36%↓

How it works

1
Day 1-2

Define Problem & Set Targets

Identify tasks, measure current processing time, agree on targets (e.g., 5min→30sec, 95%+ accuracy)

You provide
  • Current workflow description
  • 3-5 sample data
  • Measurable targets
You receive
  • Workflow analysis report
  • Automation feasibility
  • Target metrics doc
2
Day 3-10

Build System

Configure AI model, integrate APIs, build data pipeline, implement error handling, write test cases

You provide
  • API keys/access
  • More samples (if needed)
  • Mid-review (day 5)
You receive
  • Working prototype (day 5)
  • Completed system (day 10)
  • Test report
3
Day 11-13

Validate & Improve

Test with real data, measure before/after metrics, validate against targets, improve if needed

You provide
  • 20-50 real cases
  • UAT participation
  • Feedback
You receive
  • Before/after report
  • Target validation
  • Improved final version
4
Day 14

Deploy & Handover

Deploy to production, set up monitoring, provide operations manual, begin 1-month free support

You provide
  • Deploy access
  • Acceptance sign-off
  • Training attendance (1-2)
You receive
  • Live system + source code
  • Ops manual & rollback guide
  • 1-month free support starts

Security first

PII masking, least privilege, audit logs, and safe rollback.

Data protection

PII masking & encryption

Audit trail

Complete operation logs

Safe rollback

Instant state recovery

Start now.

We prove results first with a 14-day PoC.