成果物
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.
技術スタック
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.
プロセス
ワークフロー、ボトルネック、自動化の機会をマッピングします。
アーキテクチャドキュメント、インテグレーション計画、固定スコープの料金を3日以内にお届け。
毎週のデモを行う反復的なスプリント。本番対応の自動化フロー。
デプロイメント、モニタリングダッシュボード、ドキュメント作成、チームトレーニング。
HubSpot、Salesforce、Slack、Google Workspace、Notion、Airtable、およびAPIを持つあらゆるシステムと連携可能です。
はい。現在のプロセスを監査し、最もROIの高い自動化の機会を特定し、反復的に構築します。
ほとんどのプロジェクトで6〜12週間です。シンプルな単一ワークフローの自動化は3〜4週間で出荷可能。
関連する導入事例
AIリードスコアリング、自動アウトリーチシーケンス、CRM連携を構築し、手動のプロスペクティングに60%の時間を費やしていた営業チームを変革。
返信率40% · デモ予約3倍
導入事例を見る