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Ikigai: MIT-based AI Apps Startup is set to Alleviate Supply Chain Attacks with Advanced Cybersecurity

Ikigai, the MIT-based startup has developed an AI Apps platform based on the research conducted by its cofounders at MIT.


This year, the constant surge of data breaches and ransomware attacks are apparently impacting the supply chains and the manufacturers who are replying on them. VentureBeat has discovered in their research that supply chain-directed ransomware attacks have broken all previous records in the manufacturing industry, with the most severe losses occurring in the medical device, pharmaceutical, and plastics industries. The complete sum of the victim organization's cyber-insurance is being demanded as ransom by the attackers. The attackers send top management a copy of their insurance coverage if they refuse, but they are rejected.

Threat Actors Asking for Bigger Ransoms

Manufacturers who are impacted by the supply chain attacks claim the ransom demands are two to three times more than those made by other businesses. This is so because it can cost millions to shut down a production line for even a single day. Much smaller to mid-tier single-location manufacturers scramble to get cybersecurity assistance after paying the ransom discreetly. However, they are frequently victims a second or third time.

Ransomware attacks remain the cybercrime of choice for threat actors who are targeting supply chains for financial gain. Till now, the most well-known cases of such attacks have included companies like Aebi Schmidt, ASCO, COSCO, Eurofins Scientific, Norsk Hydro, and Titan Manufacturing and Distributing. The other major firms that were attacked choose to stay anonymous.

Among the manufacturing firms, A.P. Møller-Maersk, the Danish shipping giant suffered the most severe attack on a supply chain, which cost $200–300 million and temporarily shut down the major cargo facility at the Port of Los Angeles.

What is the MIT Based Start-up? 

Ikigai, the MIT-based startup has developed an AI Apps platform based on the research conducted by its cofounders at MIT with large graphical models (LGMs) and expert-in-th-loop (EiTL), through which the system can collect real-time inputs from professionals and continuously learn to maximize AI-driven insights and expert knowledge, intuition, and expertise.

The list of industries using Ikigai's AI Apps is expanding. Currently, it includes manufacturing (predictive maintenance quality assurance), retail (demand forecasting, new product launch), insurance (auditing rate-making), financial services (compliance know-your-customer), banking (customer entity matching txn reconciliation), and supply chain optimization (labor planning sales and operations planning).

Making sense of walled, incomplete data dispersed throughout the organization is a constant struggle for every enterprise. The most challenging, intricate issues that an organization faces merely amplify how broad its information gaps prevent decision-making. Manufacturers pursuing a China Plus One strategy, ESG initiatives, and sustainability have told VentureBeat that the complexity of the decisions they must make in these strategic areas is outpacing current approaches to data mining.

The LGMs used by Ikigai's AI Apps platform, which works with sparse, small datasets to give necessary insight and intelligence, aid in resolving these problems. DeepMatch for AI-powered data prep, DeepCast for predictive modeling with sparse data and one-click MLOps, and DeepPlan for reinforcement learning-based domain-specific decision suggestions are some of its features. EiTL is a sophisticated product feature made possible by Ikigai's technology.

EiTL, together with LGM models will eventually strengthen the model accuracy by integrating human expertise. To identify new risks and fraud tendencies in managed detection and response (MDR) situations, EiTL would integrate human experience with machine learning algorithms. EiTL's real-time AI system inputs have the potential to enhance MDR teams' threat identification and response capabilities.

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