IFOY Audit
Finalists undergo the three-stage IFOY Audit as part of the IFOY Audit, which takes place during the TEST CAMP INTRALOGISTICS. This consists of the scientific IFOY Innovation Check, the IFOY Test and the jury test.
AI2RampOptimizer
AI2Connect
AI2Connect is a factory for specialized AI agents in logistics. The first agent – AI2RampOptimizer – combines predictive learning, reinforcement learning, and rule-based logic in a self-learning multi-agent system for dock and ramp optimization. Results: 30% shorter waiting times, 60% lower demurrage costs, 15% CO₂ reduction. The plug-and-play system deploys in two to three weeks without IT integration and achieves Return on Investment within eight to twelve weeks.
Product name and company
AI2RampOptimizer – AI2Connect
Description
The challenge
Europe’s logistics centers struggle with labor shortages, increasing complexity, and inefficient dock processes. Dispatchers spend 60% of their time on manual coordination. The result: long waiting times, high demurrage costs, and stressed personnel. The first multi-agent system, AI2RampOptimizer, automates dock and ramp scheduling. It combines three AI approaches:
- Predictive Learning for precise arrival forecasts,
- Reinforcement Learning for dynamic optimization, and
- rule-based logic for compliance requirements.
The system analyzes real-time data from TMS/WMS, ETA signals, and historical patterns to deliver dynamic recommendations.
The solution
AI2Connect develops a modular AI agent architecture for logistics. Five specialized agents work together with a central orchestrator – from data cleaning and pattern recognition to real-time scoring and intelligent orchestration. Each agent learns continuously from results.
Measurable results
30% shorter truck waiting times, 60% lower demurrage costs, 20% higher dock utilization, 15% CO₂ reduction. A mid-sized logistics company with eight docks saves over €20,000 monthly – with an ROI of eight to twelve weeks.
Plug-&-Play implementation
Integration via REST API or CSV upload in two to three weeks, GDPR-compliant, without major IT projects. Intuitive dashboard with real-time KPIs, CO₂ tracking, and scenario simulation. Every decision is transparently traceable (Explainable AI).
The Vision
A logistics industry where AI agents support people instead of replacing them – efficient, sustainable, and fair.
The factory approach enables rapid scaling across yard management, route optimization, and further domains.
Innovations
AI2RampOptimizer is a multi-agent system for dock optimization that learns fully autonomously and continuously improves itself.
The five core innovations of AI2RampOptimizer
- Multi-Agent factory architecture: Five specialized AI agents (Data, Feature, Frame-Builder, Training, Recommendation agents) work modularly together with a central orchestrator. Each agent has a defined task and communicates via standardized interfaces. The architecture enables flexible adaptations without system restructuring.
- Continuous self-learning: After each planning cycle, the system analyzes deviations between forecast and reality, trains multiple ML models in parallel, and automatically selects the best model (Champion Selection). Optimization occurs fully autonomously – without manual model updates or reconfiguration.
- Explainable AI as core principle: Every recommendation includes a transparent rationale, a confidence score (0 tp 100%), and alternative scenarios. Dispatchers can perform what-if simulations and understand why the system makes a specific decision. Transparency builds trust.
- Plug-&-Play integration: The system integrates via REST API or CSV upload into existing IT landscapes. Deployment time: two to three weeks from contract signing to go-live. No complex adaptations of existing systems required.
Hybrid pricing model with success component: The pricing model combines setup fees with success-based components. Customers pay for measurable efficiency improvements based on defined KPIs (waiting times, demurrage, throughput). This structure creates partnership and shared interest in project success.
Market relevance
AI2Connect addresses the core players in logistics: distribution centers, freight forwarders, 3PL/4PL service providers, as well as production, FMCG, and automotive logistics. These companies struggle across Europe with acute labor shortages, increasing complexity, and inefficient dock processes. This situation leads to massive productivity losses and rising operational costs.
Market size and growth: The global market for AI in logistics is growing at 46% CAGR and will reach a volume of €37 billion by 2030. AI2Connect focuses on a European niche segment of approximately €8 billion – specialized in mid-sized logistics and forwarding companies (500 – 5,000 shipments/day) that require flexible, quickly implementable solutions without major IT projects.
Scaling strategy – white-label model: Through strategic partnerships with TMS, WMS, and YMS providers, the AI agents can be distributed as integrated modules. This B2B2C approach opens up a broad customer network via established software partners – without our own direct sales. Software providers gain an innovative differentiator, while AI2Connect gains scalable market access.
Market validation: Setlog: Cooperation since August 2025, integration in test phase; Prologistics: Pilot launch planned for February 2026. Additional prospects: Active discussions with logistics service providers and TMS vendors.
The strong response from the industry confirms: Adaptive, self-learning AI for operational logistics processes meets a real need.
As a young company (founded March 2025), AI2Connect has already established concrete partnerships and built a solid pipeline.
Customer benefits
Measurable economic impact
- AI2RampOptimizer delivers proven efficiency gains:
- 25 – 30% shorter truck waiting times – less idle time, happier drivers.
- 60% lower demurrage costs – mid-sized company saves over €20,000 monthly.
- 20% higher dock utilization – maximum throughput without additional infrastructure.
- 15% CO₂ reduction – improved ESG performance.
- ROI in eight to twelve weeks – fastest payback in the industry.
Operational excellence
- Plug-&-Play Ddeployment: Integration via REST API or CSV in two to three weeks – no IT mega-projects, no SAP modifications.
- Full transparency: Intuitive dashboard with live KPIs and CO₂ tracking. Explainable AI provides every recommendation with reasoning and confidence score – no black box.
- Continuous optimization: System learns autonomously and improves predictions after each cycle.
People-centric approach
- Dispatchers gain 2.5 hours daily for strategic tasks.
- Warehouse and dock staff benefit from predictable processes.
- Drivers experience 30% shorter waiting times.
Low-risk business model
- Hybrid pricing: Setup fee plus performance-based component – pay for measurable results instead of flat fixed costs.
Result
- Predictable, sustainable logistics processes with measurable business impact.
IFOY Innovation Check
Functionality / Type of implementation
AI2Connect’s AI2RampOptimizer is a powerful, AI-assisted recommendation system designed to help dispatchers optimize the allocation of incoming trucks to a warehouse’s loading docks. This involves the integration of six technically advanced, state-of-the-art agent systems: from data import and semantic analysis, through arrival and occupancy time forecasts, to situational ramp assignment recommendations and continuous optimization of the system to align with customer-specific workflows. A wide variety of live data, such as traffic conditions, route selection, and weather, are also incorporated into the analyses via standard interfaces.
During testing, the system consistently provided meaningful recommendations for ramp allocation in under 200 ms, while also identifying and avoiding bottlenecks. The dashboards used visualize the current situation and the recommendations for ramp assignments in a clear, easy-to-understand, and transparent manner, along with a reliability rating and the pros and cons of each decision. The comprehensive learning system is technically sound and continuously learns from customer data, the operator’s selections and feedback, and a retrospective analysis of actual operational data.
Techniques such as drift prevention, competitive comparison of multiple ML models, and unit tests ensure that the updated models represent an improvement (Note: this has not yet been verified using real-world data). The solution demonstrates a high level of compliance with current regulations, including the Cyber Security Act, the AI Act (explainability and auditability), data security, and software development quality.
Novelty / Innovation
Compared to other solutions on the market, this lean, flexible, and modular multi-agent system stands out primarily for its ability to adapt to the customer, as well as its learning capabilities and federated improvement through a pool of anonymized customer operational data. Particularly innovative is the holistic process optimization for freight forwarders and warehouse operators, which optimizes resources on both sides and contributes to environmental protection. The AI2RampOptimizer provides highly intuitive explanations of its recommendations to the operator, who can ultimately make a well-informed decision. By incorporating human experience and feedback into the process instead of relying on fully automated, potentially suboptimal decisions, the system can continuously adapt to the customer’s specific operating mode. The hybrid, performance-based pricing model is also innovative and contributes to customer acceptance.
Customer benefit
In effect, the system results in significantly more efficient docking processes (30 percent reduction in truck wait times, 30 percent increase in ramp utilization, shorter turnaround times, 40 percent reduction in misallocations) and significant cost savings of up to 60 percent. In addition, it offers significantly greater flexibility in situational planning compared to conventional manual, slot-based, or rule-based solutions, while also providing very short response times to disruptions (<5 min). The self-configuration system, based on customer data, enables fast and cost-effective implementation in two to three weeks, with Return on Investment (ROI) achieved quickly within two to three months.
Market relevance
The AI2RampOptimizer targets a relevant, mid-sized market, with a specific focus on SMEs, which often avoid the costly implementation of traditional large-scale software solutions. The goal is to achieve a 2.5 percent market share among the 85,000 companies in Germany. To achieve this, AI2Connect is selecting appropriate market entry strategies, including direct sales to end customers and white-label partnerships. The currently small number of pilot customers is expected to increase to five to ten over the next 12 months, and parallel tests with freight forwarders involving up to 50 pilots will be conducted.
IFOY verdict
The AI2Connect solution has the potential to enable its customers to achieve significantly greater efficiency in ramp allocation, thereby substantially optimizing costs, throughput, and wait times, as well as alleviating the shortage of skilled workers. The system’s scalability and market penetration currently represent the greatest challenge.
| Functionality / type of implementation | ++ |
| Novelty / Innovation | + |
| Customer benefits | ++ |
| Market relevance | + |
| ++ very good / + good / Ø balanced / – less / — not available | |
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In den Statuten sind die Grundwerte und die Standards des IFOY AWARD festgelegt, nach denen die Organisation handelt. Dazu gehören unter anderem Gremien, Wahlomodus, Bewertungskriterien sowie der Code of Conduct.
Committees
The International Intralogistics and Forklift Truck of the Year has three bodies: Jury, sponsors, and advisory board.