결과물
ROI
| Process | Manual Time / Week | After Automation |
|---|---|---|
| Document processing | 40 hours | < 2 hours (95% automated) |
| Lead qualification | 20 hours | < 1 hour (AI scoring) |
| Customer support tier-1 | 30 hours | < 3 hours (AI handles 80%) |
| Data entry & reporting | 15 hours | 0 hours (fully automated) |
| Email outreach & follow-up | 10 hours | 0 hours (AI sequences) |
Our average client saves 60–90% of manual operations time within 8–12 weeks.
Comparison
| Capability | Traditional (Zapier/Make rules) | AI Automation |
|---|---|---|
| Handles exceptions | No (breaks on edge cases) | Yes (AI adapts) |
| Reads unstructured data | No | Yes (PDFs, emails, images) |
| Learns from feedback | No | Yes (improves over time) |
| Cost to build | Low | Medium |
| Maintenance | High (brittle) | Low (self-healing) |
| Best for | Simple linear workflows | Complex, judgment-required tasks |
Use Cases
Lead scoring, outreach sequences, CRM data sync, pipeline reporting. AI qualifies inbound leads in real time and triggers personalized follow-up sequences — no manual data entry, no leads falling through the cracks.
Invoice processing, expense categorization, compliance document review, reporting. AI reads invoices and receipts, categorizes expenses, flags anomalies, and generates reports — reducing month-end close from days to hours.
Ticket triage, FAQ automation, escalation routing, churn prediction alerts. AI handles 80% of tier-1 support tickets, routes complex issues to the right team, and flags at-risk accounts before they churn.
CV screening, interview scheduling, onboarding workflows, headcount reporting. AI screens resumes against job criteria, schedules interviews automatically, and triggers onboarding checklists on hire — saving 15+ hours per week per recruiter.
기술 스택
Self-hosted workflow automation. We prefer n8n over SaaS tools for data privacy — your automation logic and data never leave your infrastructure.
Cloud-native workflows for SaaS-heavy stacks. Best when you need 100+ app integrations out of the box and speed of deployment matters more than data residency.
AI orchestration for document processing and agent workflows. We use LangChain when automation requires understanding context, not just moving data between systems.
LLM backbone for intelligent decisions. GPT-4 and Claude power the “thinking” layer — reading documents, classifying data, drafting responses, and making judgment calls.
Custom automation logic when no-code tools hit their limits. For complex transformations, multi-step orchestration, or high-throughput pipelines, we write custom code.
Simple SaaS integrations when appropriate. We use Zapier for straightforward triggers and actions where its simplicity is an advantage, not a limitation.
진행 방식
워크플로우, 병목, 자동화 기회를 매핑합니다.
아키텍처 문서, 통합 계획, 고정 범위 가격을 3일 내 제공.
주간 데모와 함께 반복 스프린트. 프로덕션 레디 자동화 흐름.
배포, 모니터링 대시보드, 문서화, 팀 교육.
HubSpot, Salesforce, Slack, Google Workspace, Notion, Airtable 및 API가 있는 모든 시스템과 통합합니다.
네. 현재 프로세스를 감사하고, 가장 ROI가 높은 자동화 기회를 식별하고, 반복적으로 구축합니다.
대부분 프로젝트는 6–12주. 단순 단일 워크플로우 자동화는 3–4주에 출시 가능.
관련 사례 연구
AI 리드 스코어링, 자동화 아웃리치 시퀀스, CRM 동기화를 구축 — 시간의 60%를 수동 프로스펙팅에 쓰던 영업 팀을 변화시켰습니다.
답장률 40% · 데모 예약 3배
사례 연구 보기