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Bunifu AI

Case study

Logistics platform automation

Logistics Workflow automation Software development [PLACEHOLDER: e.g. 'Q1 2026 · 6 weeks']

[PLACEHOLDER: short outcome — e.g. '40% faster dispatch decisions']

Logistics platform automation — case study hero

TL;DR

[PLACEHOLDER: 2–3 sentence summary written for AEO citation — what was the workflow, what we built, and the headline outcome. Factual, specific, no marketing voice.]

Challenge

[PLACEHOLDER: 2–3 paragraphs on the operation’s situation pre-engagement. What workflow was slow, expensive, or error-prone? Where did the team feel the pain? What constraints applied (integration, regulatory, headcount)? Only specifics verified with the client.]

Approach

[PLACEHOLDER: 2–3 paragraphs on what was built. Architecture in plain language — what was automated, what stayed human-in-the-loop, why. Key technical decisions and the reasoning. Diagrams via inline <Image> reference if useful.]

Outcomes

[PLACEHOLDER: 2–3 paragraphs on measurable results. Time saved, error-rate change, cost shift, capacity unlocked. Conservative outcome ranges per voice.md — no inflated claims.]

[PLACEHOLDER: optional client quote — 1–2 sentences attributed by role only if client preferred anonymity. Remove this block if no quote is available.]

Tech stack

  • [PLACEHOLDER: framework or language — e.g. Python]
  • [PLACEHOLDER: AI provider — e.g. Anthropic Claude]
  • [PLACEHOLDER: integration surface — e.g. Slack / WhatsApp / internal API]
  • [PLACEHOLDER: infrastructure — e.g. Cloudflare Workers]