AI for Maritime & Shipping with Chinese LLMs

Published August 2026 · Maritime Shipping DeepSeek

The maritime and shipping industry moves over 80% of global trade by volume, generating massive documentation: bills of lading, charter party agreements, port state control reports, customs declarations, crew certifications, and voyage logs. Chinese LLMs like DeepSeek V4, GLM-4, and Qwen3 can process this complex, multilingual, regulation-heavy environment to optimize operations, ensure compliance, and reduce administrative overhead. TokenEase's unified API provides cost-effective access to these models for shipping companies worldwide.

Why Chinese LLMs for Maritime?
Chinese LLMs excel at processing multilingual shipping documents, understanding complex regulatory frameworks across jurisdictions, and delivering results at ~40% lower cost than Western APIs. Their strength in technical reasoning makes them ideal for voyage optimization and contract analysis.

1. Voyage Optimization with Natural Language

Transform weather forecasts, port congestion data, and fuel price reports into actionable voyage recommendations.

import requests

def optimize_voyage(vessel_details, cargo_info, route_constraints, market_data):
    response = requests.post(
        "https://tokenease.io/v1/chat/completions",
        headers={"Authorization": "Bearer YOUR_TOKENEASE_API_KEY"},
        json={
            "model": "deepseek-v4",
            "messages": [
                {"role": "system", "content": "You are a maritime operations expert. Optimize voyages considering weather, fuel, port costs, and delivery deadlines. Provide route recommendations with cost estimates."},
                {"role": "user", "content": f"Vessel: {vessel_details}\nCargo: {cargo_info}\nConstraints: {route_constraints}\nMarket: {market_data}\n\nRecommend optimal voyage plan."}
            ]
        }
    )
    return response.json()["choices"][0]["message"]["content"]

vessel = "Panamax bulk carrier, 75,000 DWT, fuel consumption 35 MT/day at 12 knots"
cargo = "60,000 MT iron ore, loading Qingdao, discharging Rotterdam"
constraints = "Laycan: Sept 1-7. Max draft at discharge: 13.5m. Suez Canal transit preferred."
market = "Baltic Capesize Index: $28,500/day. Bunker price Rotterdam: $580/MT VLSFO."
plan = optimize_voyage(vessel, cargo, constraints, market)

2. Automated Port Documentation

Generate pre-arrival notifications, customs declarations, and port state control documentation from voyage data.

def generate_port_docs(voyage_data, port_requirements, vessel_certificates):
    response = requests.post(
        "https://tokenease.io/v1/chat/completions",
        headers={"Authorization": "Bearer YOUR_TOKENEASE_API_KEY"},
        json={
            "model": "qwen3-235b",
            "messages": [
                {"role": "system", "content": "Generate complete port arrival documentation packages. Include all forms required by the port authority and flag state."},
                {"role": "user", "content": f"Voyage: {voyage_data}\nPort requirements: {port_requirements}\nCertificates: {vessel_certificates}\n\nGenerate pre-arrival notification and required forms."}
            ]
        }
    )
    return response.json()["choices"][0]["message"]["content"]

voyage = "MV Pacific Star, IMO 9876543, ETA Singapore Aug 25 0600, last port: Busan"
port_req = "Singapore MPA: Advance notification 72hrs, crew list, cargo manifest, ballast water report"
certs = "Class: Lloyd's Register. DOC valid until 2027. SMC valid. ISSC valid until 2026-11."
docs = generate_port_docs(voyage, port_req, certs)

3. Cargo Compliance & Hazardous Materials Classification

Verify cargo declarations against IMDG codes, ensure proper segregation, and generate dangerous goods documentation.

def check_cargo_compliance(cargo_declaration, vessel_layout, imdg_references):
    response = requests.post(
        "https://tokenease.io/v1/chat/completions",
        headers={"Authorization": "Bearer YOUR_TOKENEASE_API_KEY"},
        json={
            "model": "glm-4-plus",
            "messages": [
                {"role": "system", "content": "Check cargo compliance against IMDG Code. Identify segregation violations, missing documentation, and stowage hazards."},
                {"role": "user", "content": f"IMDG refs: {imdg_references}\nVessel layout: {vessel_layout}\nCargo: {cargo_declaration}\n\nCheck compliance and list issues."}
            ]
        }
    )
    return response.json()["choices"][0]["message"]["content"]

cargo = """
Container 1: UN 1203, Gasoline, Class 3, PG II, 20,000L
Container 2: UN 1789, Hydrochloric acid, Class 8, PG II, 15,000L
Container 3: UN 1950, Aerosols, Class 2.1, 5,000kg
"""
layout = "Holds 1-5 available. Container 1 stowed Hold 3. Container 2 stowed Hold 4."
imdg = "Segregation Table: Class 3 and Class 8 require 'Separated from' minimum."
compliance = check_cargo_compliance(cargo, layout, imdg)

4. Crew Management & Certification Tracking

Track crew certifications, flag state requirements, and generate watch schedules compliant with STCW regulations.

def check_crew_compliance(crew_list, flag_state_requirements, voyage_duration):
    response = requests.post(
        "https://tokenease.io/v1/chat/completions",
        headers={"Authorization": "Bearer YOUR_TOKENEASE_API_KEY"},
        json={
            "model": "kimi-k2",
            "messages": [
                {"role": "system", "content": "Check crew compliance against STCW and flag state requirements. Identify expired certificates, insufficient manning, and rest hour violations."},
                {"role": "user", "content": f"Flag state: {flag_state_requirements}\nVoyage: {voyage_duration}\nCrew:\n{crew_list}\n\nCheck compliance."}
            ]
        }
    )
    return response.json()["choices"][0]["message"]["content"]

crew = """
Master: COC valid until 2027-03, GMDSS expired 2026-06
Chief Officer: COC valid, Tanker endorsement valid
AB Seaman: BST expired 2026-05
Engineer: ETO certificate valid, medical valid
"""
flag = "Liberian flag: Minimum 8 crew for this vessel type. All certificates must be valid per STCW A-VI/1."
voyage = "45-day voyage, trans-Pacific route"
check = check_crew_compliance(crew, flag, voyage)

5. Vessel Maintenance Log Analysis

Extract maintenance insights from engine logs, inspection reports, and defect lists to predict maintenance needs.

def analyze_maintenance_logs(log_entries, class_society_rules, last_drydock):
    response = requests.post(
        "https://tokenease.io/v1/chat/completions",
        headers={"Authorization": "Bearer YOUR_TOKENEASE_API_KEY"},
        json={
            "model": "deepseek-v4",
            "messages": [
                {"role": "system", "content": "Analyze vessel maintenance logs to identify trends, predict failures, and recommend repairs before next survey."},
                {"role": "user", "content": f"Last drydock: {last_drydock}\nClass rules: {class_society_rules}\nLogs:\n{log_entries}\n\nPredict maintenance needs and survey readiness."}
            ]
        }
    )
    return response.json()["choices"][0]["message"]["content"]

logs = """
Aug 18: Main engine turbocharger vibration high (12mm/s), recommended inspection
Aug 15: Bilge pump #2 failure, replaced seal
Aug 10: Hull coating blistering noted on port side ballast tanks
Aug 5: Crane hydraulic hose leak, temporary repair applied
"""
class_rules = "Lloyd's: Special Survey due 2027. Intermediate Survey 2025 completed."
drydock = "June 2024"
maintenance = analyze_maintenance_logs(logs, class_rules, drydock)

6. Freight Contract Analysis

Extract key terms, identify risks, and compare charter party agreements against market standards.

def analyze_freight_contract(contract_text, market_comparison, previous_fixtures):
    response = requests.post(
        "https://tokenease.io/v1/chat/completions",
        headers={"Authorization": "Bearer YOUR_TOKENEASE_API_KEY"},
        json={
            "model": "qwen3-235b",
            "messages": [
                {"role": "system", "content": "Analyze maritime freight contracts. Extract key terms, identify unfavorable clauses, and compare against market benchmarks."},
                {"role": "user", "content": f"Previous fixtures: {previous_fixtures}\nMarket: {market_comparison}\nContract:\n{contract_text}\n\nAnalyze and flag risks."}
            ]
        }
    )
    return response.json()["choices"][0]["message"]["content"]

contract = """
TIME CHARTER: MV Ocean Trader
Period: 11 months +/- 30 days
Hire: $22,500/day
Off-hire: All time lost due to breakdowns, inspections, or crew issues
Delivery: Singapore, DOP Aug 25
Redelivery: Singapore or Japan range
Performance: Speed 13kn, consumption 28 MT IFO + 2 MT MGO
"""
market = "Similar Capesize vessels fixing at $24,000-26,000/day for 12-month periods"
prev = "Previous fixture: $21,000/day, 12 months, same trading area"
analysis = analyze_freight_contract(contract, market, prev)

Maritime AI Implementation Best Practices

TokenEase for Maritime Operations:
Process charter party agreements, port documentation, and compliance reports at ~40% lower cost than Western APIs. TokenEase's unified API supports DeepSeek, GLM-4, Qwen3, Kimi, and more, with automatic failover for uninterrupted operations across global shipping lanes.

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