ERP for Carbon
Transform your fleet operations with AI-powered carbon accounting, route optimization, and predictive maintenance. Align with GHG Protocol, CSRD, and global sustainability frameworks while reducing emissions and costs.
Transform your operations into ethical, sustainable, AI-enhanced logistics by aligning with Alive's 7 Standards and full Value Chain. This is part of Alive's mission, you can adapt to it.
Real-time emissions tracking for delivery fleets using CSRD metrics and GHG Protocol standards for comprehensive Scope 1-3 emissions monitoring.
AI-powered route planning that reduces fuel consumption, minimizes emissions, and improves delivery efficiency across your entire fleet network.
Extend asset life and reduce downtime with AI-driven predictive maintenance, lowering operational costs and environmental impact.
Automated compliance reporting for supply chains, integrating SASB standards and aligning with PRI sustainable lending and EU taxonomy.
We provide the solutions — you get to choose. Click on the principles below to discover their connections and build your transformation roadmap.
Replace passive ERP with context-aware, predictive decision systems
Integrate AI as core feature matching 2026 logistics standards
Automate 60%+ of decisions across fleet, routing, and warehousing
Scalable hybrid infrastructure for multi-site coordination
Live KPI tracking shortening decision cycles by 25%+
Connect sensors on vehicles and warehouses to ERP
Embed sustainability tracking and carbon emissions monitoring
Automate procurement, scheduling, billing, and exception handling
Preconfigured logistics features reducing setup by 35%
Mobile-first dashboards for field teams and drivers
AI-based anomaly detection and identity validation
Autonomous AI agents executing actions, not just reporting
Systems that learn, adapt, and guide operations
Guide adoption of AI, cloud, IoT, and sustainability
Click on any principle above to begin building your transformation roadmap. Discover how each principle connects to create an integrated, intelligent logistics ERP system for 2026.
Fulfill 5 out of 7 requirements to achieve Alive Verified status. These standards transform logistics from reporting to doing, avoiding regulatory risks and unlocking long-term value.
Integrating GRI standards into core logistics practices effectively.
1.1 Sustainability Reporting Framework
Develop framework aligned to GRI standards. Report sustainability KPIs: carbon footprint, fuel usage, and route efficiency. Train teams on these standards for logistics operations.
1.2 Regular Materiality Analysis
Run stakeholder assessments with customers, carriers, and partners to identify material logistics sustainability issues and optimize supply chain procurement.
Implementing circular economy practices across fleet operations.
2.1 Fleet Lifecycle Management
Design vehicle procurement for durability, modularity, and recyclability. Maximize fleet utilization and end-of-life vehicle component reuse.
2.2 Fleet-as-a-Service Models
Shift to leasing, subscription, or shared fleet models to maintain control for refurbishment and extend vehicle lifecycle.
Investing in energy-efficient AI for logistics sustainability.
3.1 Low-Power AI Models
Develop lightweight AI models for route optimization and fleet management using pruning and quantization to reduce energy consumption.
3.2 Renewable-Powered Infrastructure
Deploy AI infrastructure powered by renewable energy. Partner with carbon-neutral cloud providers for logistics analytics and tracking systems.
Utilizing green data centers for efficient fleet data management.
4.1 Green Data Centers
Migrate fleet tracking and logistics data to energy-efficient data centers using renewable energy, certified with LEED or ISO 50001.
4.2 Data Minimization
Implement strict data policies to collect only essential fleet and route data, reducing energy consumption and emissions from data storage.
Utilizing AI technologies for sustainable logistics innovation.
5.1 AI for Sustainable Fleet Design
Use AI-powered simulation tools to optimize fleet composition, minimize fuel use, and ensure vehicle recyclability across the lifecycle.
5.2 AI for Supply Chain Optimization
Deploy AI analytics for optimizing logistics, reducing transportation emissions, improving inventory management, and monitoring supplier environmental performance.
Extending circular economy practices with AI in logistics.
6.1 Automated Waste Management
Deploy AI for improved sorting and recycling of logistics packaging materials, using computer vision and machine learning for efficient material separation.
6.2 Predictive Fleet Maintenance
Implement AI predictive maintenance tools to monitor fleet equipment, identify imminent failures, extend asset life, and reduce downtime through optimized repair scheduling.
Structuring AI governance for ethical logistics operations.
7.1 AI Ethics Committee
Create an AI ethics committee to guide development and implementation of AI in logistics. Ensure all initiatives meet ethical, sustainability, and regulatory requirements.
7.2 Explainable AI Practices
Design transparent AI models that provide clear insights on routing and fleet decisions. Audit systems regularly to identify and overcome biases affecting sustainability efforts.
The Execution Engine: From AI Models to Sustainable Logistics
Develop AI models for carbon accounting and route optimization
Deploy AI systems across fleet operations and supply chains
Integrate Alive Standards into audit software and reporting
License carbon accounting tools to logistics providers
Generate GHG Protocol compliant emissions reports
Optimize routes and reduce emissions through AI insights
Deliver efficient, low-carbon transportation solutions
Match sustainable fleet capacity with customer demand
Provide carbon-neutral and low-emission delivery options
Enable customers to choose sustainable logistics providers
Deliver value through competitive pricing and sustainability
Generate revenue from carbon accounting and optimization platforms
Reinvest in AI development and sustainability initiatives
Revenue from digital platforms reinvests into AI research and development, creating a sustainable cycle of innovation, improved logistics operations, and environmental impact reduction.
Alive Logistics aligns with comprehensive international standards for carbon reporting, sustainable business practices, and ethical AI implementation.
Alive Verified Requirements (AVRs)
17 UN Sustainable Development Goals
Paris Agreement
GHG Protocol
Principles for Responsible Investment (PRI)
UN Guiding Principles on Business and Human Rights
"Doing Business with Respect for Human Rights" Guidance
WCED Report
Global Reporting Initiative (GRI) Standards
Climate Disclosure Standards Board (CDSB)
International Financial Reporting Standards (IFRS)
Carbon Disclosure Project (CDP)
Sustainability Accounting Standards Board (SASB)
Science Based Targets initiative (SBTi)
TCFD Framework
ISO 26000
International Integrated Reporting Framework (IIRF)
Data Protection Impact Assessment (DPIA)
CNIL Privacy Impact Assessment (PIA)
EU Non-Financial Reporting Directive (NFRD)
Corporate Sustainability Reporting Directive (CSRD)
EU Taxonomy
IFRS Constitution
EU Artificial Intelligence Act
EU General Data Protection Regulation (GDPR)
These frameworks ensure that Alive Logistics meets the highest standards for carbon accounting, ethical AI implementation, and sustainable logistics operations while maintaining compliance with global regulations.
Global trade rules meet AI-powered logistics. Automate compliance, calculate risk, optimize costs, and prepare for 2030 with intelligent Incoterms® management.
Incoterms® are global trade rules published by the International Chamber of Commerce (ICC) that define roles, responsibilities, costs, and risk transfers between buyers and sellers in international transactions.
Current Edition: Incoterms® 2020 (effective January 1, 2020) — the ninth revision with 11 terms covering multimodal and sea-only transport.
Next Revision: Expected between 2029–2030, likely addressing digital trade docs, autonomous transport, and environmental compliance.
Seller makes goods available at their premises. Buyer handles all transport and risk.
Seller delivers goods to carrier nominated by buyer at agreed place.
Seller pays for carriage to destination, but risk transfers earlier.
Seller pays for carriage and insurance to destination.
Seller delivers when goods are at buyer's disposal at named destination.
Seller delivers and unloads at named destination.
Seller bears all costs and risks to deliver goods cleared for import.
Seller delivers when goods placed alongside vessel at named port.
Seller loads goods on vessel nominated by buyer at loading port.
Seller pays freight to destination port, but risk transfers at loading.
Seller pays freight and insurance to destination, risk transfers at loading.
Traditional logistics companies miss critical AI-powered enhancements. Alive prepares you for 2030.
Automatically detect mismatches between selected Incoterms and shipment types. Flag outdated practices like FOB for containers.
Calculate risk levels: port congestion, geopolitical factors, carrier reliability, routing volatility, fuel costs, carbon intensity.
Integrate emissions data into term selection. Suggest greener alternatives (e.g., FCA vs EXW) to reduce carbon footprint.
Auto-identify required documents per Incoterm. Generate Bills of Lading, invoices, packing lists. Validate A1-A10/B1-B10 obligations.
Simulate 'What if we switch to CIF?' scenarios. Adjust risk windows, recalculate landed costs, show cash flow and time impact.
Prepare for digital trade docs, autonomous transport rules, security obligations, and potential Green Incoterms.
They Miss:
They Risk:
Transform your fleet operations with AI-powered carbon accounting. Determine if your current practices meet existing sustainability standards and will continue to do so over the next 10 years.
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