Build knowledge-based AI assistants. Call them via API.

The challenge of information silos in logistics

When a logistics manager tries to resolve a customs discrepancy or verify a specific carrier's surcharge policy, they hit a wall of fragmented documentation. In the fast-moving world of global trade, missing a single line of a compliance manual or a regional tax update doesn't just cause a delay—it risks hefty fines and broken SLAs.

The daily cost of document hunting

For most logistics firms, tribal knowledge is the only bridge between disparate PDFs, spreadsheets, and internal wikis. Senior dispatchers are constantly interrupted to answer routine questions about Incoterms or specific warehouse protocols, creating a massive bottleneck. This locked company knowledge leads to inconsistent customer advice and slow response times that can exceed three hours for simple billing queries, directly impacting your bottom line.

Why the tools they've tried fall short

Many firms have attempted to solve this with basic search tools or generic AI, only to find they aren't built for the industry's complexity:

• Internal wikis and keyword search: These require users to know exactly what they are looking for. They fail when a user asks a conceptual question like "what is the procedure for hazardous goods in the Rotterdam port?" if that exact phrasing isn't indexed.
• Generic AI (ChatGPT): Without context, these models hallucinate. In logistics, a "plausible-sounding" answer about a maritime regulation is more dangerous than no answer at all. They also present significant privacy risks for sensitive client contracts.
• No-API tools (NotebookLM): While tools like NotebookLM are great for individual research, they lack the programmatic access needed to power a real-time tracking portal or an automated helpdesk. You cannot bridge them into your existing TMS (Transport Management System).

What's missing is a way to turn static freight documents into an active, programmatic knowledge base.

How knowledge retrieval powers logistics workflows

What smart knowledge retrieval actually does

Lookio uses Retrieval-Augmented Generation (RAG) to bridge the gap between your raw data and actionable answers. Instead of trying to "train" a model on your shipping manuals—which is slow and static—Lookio processes your documents into searchable chunks.

Think of it like a veteran logistics coordinator who has read every one of your contracts and SOPs. When you ask a question, the system doesn't guess based on the internet; it pulls the exact three paragraphs from your specific carrier agreement to generate a sourced response. This ensures that every answer is grounded in the official documentation you provided.

A real scenario for freight forwarders

When a customer asks about a specific peak season surcharge via your portal, the system calls the Lookio API. Lookio instantly searches your uploaded rate cards, retrieves the specific pricing logic, and returns a verified answer to your helpdesk in seconds. This allows junior staff to handle expert-level inquiries with the precision of a senior manager.

Connect it to how you already work

Lookio is built to live wherever your data is needed, offering four distinct integration paths:

• Via API: Automate complex document checks inside your n8n workflows or Make scenarios.
• Via Embeddable Widget: Drop a self-service AI assistant onto your client portal or internal tracking page in minutes to reduce support volume.
• Via MCP Server: Connect your logistics knowledge base directly to AI agents like Claude, allowing them to "read" your port maps or rate schedules during complex planning tasks.
• Via CLI: Use the command line with JSON output to bulk-process shipping manifests or compliance documents without human intervention.

The Lookio advantage

Lookio wins by offering an API-first architecture that traditional search tools lack. By combining precise vector search with flexible pay-as-you-go pricing, you can scale from one assistant for HR policies to a hundred assistants—one for every major shipping lane or client contract—without the enterprise overhead.

Building your logistics assistant and making it production-ready

Step 1: Connect clean logistics data

Start by gathering documents that represent your unique expertise: SOPs, carrier contracts, port regulations, and customs guides. Lookio supports PDF, Docx, and even Sitemap Syncing—if your rates are on a password-protected portal, simply sync the URL and Lookio handles the updates. Avoid dumping everything into one bucket; create separate Assistants for "Customs Compliance," "Carrier Contracts," and "Internal HR."

Step 2: Configure your Assistant

Give your Assistant a specific persona. For a logistics use case, a system prompt might look like this:

"You are a Logistics Compliance Expert. Use only the uploaded port regulations and carrier agreements to answer. If a specific surcharge is not mentioned in the documents, state that it must be verified manually with the carrier. Always cite the specific document name and page number."

Choose your query mode based on the urgency:

• Flash (30 credits): Use this for customer-facing tracking bots where speed is vital.
• Deep (80 credits): Recommended for complex content generation or auditing thousand-page freight contracts where precision is non-negotiable.

Step 3: Integrate and optimise

Connect Lookio to your daily tools. You can use our n8n templates to link your Assistant to Slack or your TMS via the API. Monitor the Lookio dashboard to see which documents are being queried most often—this usually highlights where your staff needs more training or where documentation is lacking.

Mistakes that kill retrieval quality

• Vague Instructions: Don't say "be helpful." Say "Provide answers in structured bullet points for shipping quotes."
• Messy PDFs: Avoid uploading scans with heavy handwriting or low-quality OCR, as this breaks the chunking strategy.
• Mixing Domains: Don't put your "Holiday Policy" in the same Assistant as your "Hazardous Materials Guide." Narrowing the search space significantly increases retrieval accuracy.
• Ignoring Sources: Always require the Assistant to quote its source, ensuring that your team can verify the sourced insights before sending them to a client.