AI automation for logistics ops with integration-heavy experience
Quote intake structuring, dispatch log summarisation, customer communications automation. Built by the engineer behind bolttech's 40+ provider integrations. $3,000/mo.
Who this is for
Ops director at a $10M to $100M logistics operator where dispatch chat logs are messy, quote intake is manual, and customer comms are repetitive.
The pain today
- Dispatch chat logs (WhatsApp, email) are messy and lose context
- Quote intake from emails takes hours to structure
- Customer communications (shipment status, ETA) are repetitive
- Integration with TMS and accounting blocks more automation
- No ML team internally to set up AI carefully
The outcome you get
- AI automations for logistics ops on $3,000/mo retainer
- Quote intake structuring from email and document inputs
- Dispatch-log summarisation for ops visibility
- Automated customer comms (status, ETA, delay alerts)
- Integration with TMS and accounting (from bolttech playbook)
Where logistics AI actually pays back
Three places deliver clear ROI. Quote intake — LLM reads incoming quote requests (email attachments, PDFs, form submissions), extracts origin, destination, commodity, weight, service-level, and routes to appropriate sales rep. Cuts intake time 60 to 80 percent. Dispatch-log summarisation — end-of-day summary of dispatch chat traffic (WhatsApp, Slack, email) for ops manager review. Catches issues that scattered messages miss. Customer communications — proactive status updates, ETA notifications, delay alerts drafted and sent automatically with human oversight.
Chat-log and document intake patterns
Dispatch operations run on messaging apps. LLM reads dispatch chat, extracts structured events (pickup confirmed, delivery made, delay reported, exception). Feeds events into TMS or custom ops dashboard. For operators with 10+ dispatchers using WhatsApp, this is transformative — scattered context becomes structured events. Document intake (bills of lading, customs docs, invoices) extracts key data for TMS entry. Human verification before committing to systems of record.
Integrations with TMS and accounting
TMS: Cargowise, MercuryGate, Turvo, Magaya, McLeod. Accounting: QuickBooks, Xero, Sage. AI-extracted data flows into TMS and accounting via API. For TMS without good APIs, structured file integration or middleware. At bolttech I ran integration work against 40+ payment providers — same discipline applies: unified interface behind disparate external systems, idempotent writes, aggressive error handling. Logistics integrations layer AI extraction on top of that foundation.
Pricing and engagement model
$3,000/mo retainer. Covers AI integration, prompt engineering, TMS integration, monitoring, iteration. 14-day money-back guarantee. Cancel anytime. 100 percent code ownership under Work Made for Hire. LLM costs pass through. For operators with very high document or message volume, cost optimisation (batching, caching, routing) matters monthly. Subscription works well for logistics because ops automation grows organically — new integration, new extraction type, new report type come up monthly.
Case: bolttech and Instill
bolttech: $1B+ unicorn payment service with 40+ provider integrations, 99.9 percent uptime, zero post-launch critical bugs (NestJS, React, MongoDB, Redis, TypeScript). Integration-heavy operations discipline transfers directly to logistics. Instill: self-initiated AI skills platform with structured-prompt library (30+ users, 1,000+ skills saved). Pattern for AI-driven ops. Between them, the logistics AI territory is covered — reliable integration work plus structured AI automation.
When a TMS-bundled AI feature covers it
Modern TMS platforms are adding AI features (Turvo, Cargowise, Samsara AI). For operators happy with their TMS's native AI, bundled features may cover the need at no extra cost. My retainer pays back when TMS AI is limited or absent, when operators have specific workflow needs, or when integration-heavy automation across systems matters. I help evaluate in the first call. Often the honest answer is 'your TMS already does this; enable it and save the retainer.'
Recent proof
A comparable engagement, delivered and documented.
Unified payment orchestration across Asia and Europe
Delivered the payment orchestration platform at bolttech, a $1B+ unicorn, with 40+ integrations across multiple regions.
Frequently asked questions
The questions prospects ask before they book.
- Can you integrate with our TMS?
- Yes. Cargowise, MercuryGate, Turvo, Magaya, McLeod, Rose Rocket, Samsara — all have API or file-based integration paths. For API-first TMS, AI outputs flow into TMS records directly. For legacy TMS, structured file or middleware integration. Initial TMS integration: 3 to 6 weeks. Ongoing integration of new AI-driven data points: smaller additions, days each.
- How does document intake work?
- Incoming documents (bills of lading, customs declarations, invoices, rate agreements) come via email, upload, or EDI. LLM with vision extracts key data (shipper, consignee, commodity, weights, reference numbers). Structured output validates against TMS master data. Human verification on ambiguous fields before writing to TMS. For high-volume operators with thousands of documents monthly, AI extraction is the difference between ops team spending days on typing and being on value-add activities.
- Can AI handle real-time dispatch decisions?
- Not fully. Dispatch decisions require context AI does not have — driver relationships, customer priorities, local knowledge. AI can surface suggestions (load pairing, driver assignment based on location and hours), but human dispatchers make final calls. For complex operations, full dispatch automation is dangerous — mistakes compound quickly. AI as decision support works well; AI as autonomous dispatcher does not.
- What about ELD or telematics integration?
- Samsara, Geotab, Motive — all have APIs. AI can consume location, speed, and status data to generate ETAs and detect exceptions (stopped longer than expected, delayed arrival predicted). AI does not make HOS or ELD compliance decisions — that remains in the regulated ELD system itself. AI surfaces insights on top of telematics data for dispatcher review.
- How much do API costs run?
- Typical logistics AI: $200 to $1,000/month in LLM and transcription API costs. Document extraction at $0.01 to $0.10 per document. Dispatch log summarisation at $1 to $5 per dispatcher per day. Customer communication drafting at $0.02 to $0.20 per message. For operators with large volumes, cost optimisation matters — batch processing, caching, model routing. Tracked monthly to ensure automations earn their cost.
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