Introduction
In fast-moving transport, logistics, and 3PL operations, the burden of document processing, validation, and data entry can slow teams down, introduce errors, and distract from strategic priorities. Qargo Intelligence (Qi) is designed to take on that load. Qi is the AI-powered engine built into Qargo’s TMS platform, focused on automating the “busywork” and elevating user productivity, consistency, and accuracy.
Behind every feature of Qi lies a principle: remain human-centric. Qi is not about replacing expert planners and auditors — it’s about enabling them to work smarter, handling low-value repetitive tasks so they can focus on exceptions, decisions, and exceptions handling.
This overview covers Qi’s functions across document intelligence, subcontractor/customer profiling, and validation workflows — and highlights five key features that make Qi a powerful tool in transport operations.
Key Features of Qi
Feature | What It Does | Why It Matters | Learn More |
Document Intelligence (data extraction & matching) | Qi ingests uploaded documents (PDFs, scans, images) and extracts structured data (e.g. container IDs, seal numbers, references) and matches documents (e.g. PODs) to orders/trips. | Eliminates manual retyping, accelerates document processing, and reduces human error. Focuses human effort on what matters most, improving throughput and reducing fatigue. |
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Validation task automation | Qi drives and coordinates validation workflows: comparing document data to order/trip data, flagging mismatches or missing elements, and routing tasks to users. | Streamlines the quality control step and reduces bottlenecks in approvals and exception handling. |
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Automated subcontractor & customer summaries (company intelligence) | Qi automatically enriches newly added subcontractor or customer contacts with public, verified data — e.g. company size, turnover, industry activity. | Accelerates onboarding, enables faster decision making, and helps avoid manual lookups. |
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Exception / alert handling & review prioritisation | Rather than making users wade through all data, Qi highlights anomalies and exceptions (e.g. missing fields, mismatches) and surfaces them for review. | Focuses human effort on what matters most, improving throughput and reducing fatigue. |
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When combined, these features allow Qi to cover the full chain: ingesting documents, extracting and matching data, flagging issues, enriching partner profiles, and helping the operations team validate and approve with confidence.
Terminology / Glossary
To help users interpret Qi’s outputs and features, here’s a glossary of key terms:
Term | Definition / Meaning in Qi Context |
POD | Proof of Delivery document (signed by driver/consignee) used to confirm service delivery. |
CMR | Convention on the Contract for the International Carriage of Goods by Road document, commonly used in cross-border road transport. |
Seal number / container ID | Unique identifiers affixed to containers or seals, often critical for matching shipments and ensuring integrity. |
Validation Task | A flagged discrepancy or missing item created by Qi requiring human review (e.g. mismatch between extracted data and system record). |
RAG / Grading / Quality Flagging | A visual scheme (Red, Amber, Green) Qi uses to rate the quality or completeness of documents. “Green” means acceptable, “Amber” means minor issues, “Red” means significant problem needing correction. |
Partner summary / profile enrichment | The automatic gathering and display of public/business data (turnover, employee count, industry sector) about subcontractors or customers. |
Exception handling / “review by exception” | The principle of Qi surfacing only the problematic or irregular items to human users, while passing through items that fully comply. |
How Qi Fits Together (Workflow Perspective)
Here’s a simplified sketch of how Qi’s components operate in a real workflow:
Document upload / ingestion
A user (or driver) uploads a POD, CMR, scanned image or PDF. Qi ingests it and begins parsing relevant fields.Extraction & matching
Qi extracts key values (seal numbers, container IDs, references) and attempts to match that document to existing job/trip records in the system.Completeness check
Qi inspects for legibility, and completeness. Documents that fall short are flagged (e.g. red or amber status).Validation task execution
QI validation task where scheduled in the workflow, are executed and the appropriate label is applied. Visual alert for users that items require manual review (operations, finance, etc.) and further investigation.Review & resolution
The user can direct their attention to flagged items or tasks; approved documents, with no issues, may proceed automatically. The user can override, edit, or confirm as needed.Enrichment of partner profiles
Meanwhile, when a new subcontractor or customer is added into the system, Qi fetches public business data to build a summary profile automatically — no manual research needed.
Benefits & Impact
Efficiency gains: By automating data entry, signature checks, document matching, and validation routing, Qi reduces clerical burden on operations and finance teams.
Error reduction and consistency: Automated extraction and rules-based validation reduce human mistakes and ensure uniform checks.
Faster onboarding & profiling: Partner summaries let teams assess subcontractors or customers instantly without tedious manual lookup.
Better audit performance and traceability: Qi’s flagging and task history provides an audit trail, and users always know which items needed attention.
Focus on high-value work: Because Qi handles the bulk of clean, straightforward documents automatically, human effort is freed to focus on exceptions and higher-value decisions.
Qargo Intelligence (Qi) is more than just a “smart assistant” — it’s the backbone of an automated, exception-driven workflow for transport operations. With document intelligence, validation orchestration, signature detection, and partner profiling, Qi helps organisations scale without proportionally increasing back-office staff.