As supply chains face growing pressure to move faster, operate leaner, and manage rising volumes of data, a new Berlin based startup is stepping forward with an AI driven solution built specifically for operational execution. GeneralMind, which aims to automate the unstructured coordination work that keeps modern supply chains running, has secured significant early funding to scale its technology across Europe.
Strong Investor Backing for Early Stage Vision
GeneralMind has closed a twelve million dollar equity financing round led by Lakestar, Leo Capital, LucidCapital, Heliad and BOOOM. The round also attracted notable angel investors including Alexander Kudlich, Jens Urbaniak and Samir Sood. Securing this level of support within the company’s first months of operation signals strong market belief in the need for automation at the intersection of logistics, procurement, finance and enterprise systems.
The Gap Between Data and Execution
Across industries, enterprises continue to depend on traditional systems of record such as ERP platforms to track transactions and store data. However, these systems are rarely designed to handle the day to day coordination required to execute supply chain tasks. As a result, teams often fall back on email threads, shared spreadsheets and informal communication to manage exceptions, approvals and handovers.
This creates a fragmented operational environment where work is tracked in inboxes rather than in structured systems. The consequences often include missed actions, delays, inconsistent data and limited visibility, especially when multiple internal teams and external partners must collaborate in real time.
An AI System of Action
GeneralMind aims to address this gap with an AI based system designed not just to analyse information, but to act on it. The company’s AI Autopilot automates repetitive workflows that typically originate in email or spreadsheets and bridges them directly into ERP platforms and other enterprise tools.
When a task arrives, the AI captures it, interprets the intent, and carries it through to completion while keeping humans in a supervisory loop. This approach is particularly effective in environments with recurring high volume processes, strict deadline requirements or heavy compliance workloads. Use cases span sales operations, procurement, logistics coordination and invoice handling.
By creating an intelligent execution layer that works across fragmented tools, GeneralMind aims to reduce manual workload, improve accuracy and increase overall operational performance.
Addressing Long Standing Operational Pain Points
Founder and chief executive Tushar Ahluwalia explains that organisations often know where operational bottlenecks are forming, but struggle to translate that awareness into reliable execution. Drawing on his experience in e commerce, he notes that manual processes, inbox driven actions and the constant back and forth between unstructured communication and enterprise systems create major inefficiencies in large organisations.
Ahluwalia emphasises that GeneralMind is built as an end to end execution engine, not as a traditional productivity assistant. The goal is to run processes automatically with human oversight, allowing teams to focus on strategic work rather than repetitive coordination tasks.
Scaling Across Europe
The funding round, completed within the company’s earliest months, will support the scaling of GeneralMind’s technology across European markets. Investment will be directed toward developing the Autopilot system further, deepening integrations with enterprise software and expanding the operational environments where the platform can be deployed.
With global supply chains becoming more complex and the cost of operational inefficiency rising, GeneralMind sees a significant opportunity to build the core automation layer that many organisations are currently missing. By transforming how recurring tasks are executed, the startup aims to play a central role in modernising supply chain operations across Europe.
GeneralMind’s rapid rise highlights a growing shift in enterprise automation, where AI is evolving beyond insights and recommendations to take on direct responsibility for executing work. If successful, its system of action could reshape how companies manage the daily tasks that keep supply chains moving.
