Core Mission and Innovation

Traditional functional safety analysis?such as Failure Mode and Effects Analysis (FMEA)?has historically been a labor-intensive process, requiring weeks of manual data entry and human expertise to identify potential design flaws. As modern products incorporate thousands of electronic components, legacy approaches have become a significant bottleneck.

Modelwise addresses this through its "mathematically complete" approach to safety assessment. Unlike probabilistic or "black-box" AI, Modelwise utilizes formal methods and qualitative models to provide white-box reasoning. This ensures that every safety claim can be mathematically proven and explained, which is essential for certification in safety-critical industries.

The Flagship Product: Paitron

Paitron is Modelwise's flagship functional safety suite. It is designed to act as a "spell checker for engineering models," providing a seamless, automated workflow for safety engineers.

1. Automated Analysis Types

Paitron supports the most critical safety analysis standards used in global manufacturing: * FMEA (Failure Mode and Effects Analysis): Identifying potential failure modes and their impact on system behavior. * FMEDA (Failure Mode, Effects, and Diagnostic Analysis): An extension of FMEA that accounts for the diagnostic capabilities of a system, crucial for ISO 26262 and IEC 61508 standards. * FMECA (Failure Mode, Effects, and Criticality Analysis): Categorizing failure effects based on their severity and occurrence rate.

2. Technical Integration and Workflow

Paitron distinguishes itself by integrating directly into an engineer's existing toolchain, avoiding the need for "media breaks" (manual data transfers between different software). * Supported Interfaces: The software interfaces with popular Computer-Aided Engineering (CAE) and Electronic Design Automation (EDA) tools, including Matlab Simulink, Altium Designer, OrCAD PSpice, LTspice, and Siemens Xpedition. * Model-Based Failure Propagation: By analyzing the netlist and Bill of Materials (BOM), Paitron automates the evaluation of roughly 80% to 90% of failure modes. * Component Libraries: Modelwise maintains a continuously expanding database of component failure modes, allowing for rapid "matching" during the import phase.

3. Quantitative Benefits

• Speed: Reduces safety analysis cycles from several weeks to just a few hours.
• Cost Efficiency: Saves up to 80% of costs by identifying critical design flaws in the early stages of development.
• Accuracy: By eliminating human oversight and "sneak paths" (unintended circuit paths), the software often identifies risks that manual assessments miss.

Industry Applications and Standards

Modelwise's technology is tailored to meet the rigorous demands of regulated industries: * Automotive (ISO 26262): Automating safety checks for Advanced Driver Assistance Systems (ADAS) and electric vehicle (EV) powertrains. * Industrial Automation (IEC 61508): Ensuring the reliability of programmable electronic safety-related systems. * Aviation & Aerospace (ARP 4761): Managing complex system safety assessments for next-gen mobility. * Medical Devices (IEC 62304): Accelerating the development of life-critical medical technology through the TED-Med (Trusted Engineering Design for Medical Devices) consortium.

Strategic Partnerships and Recognition

Modelwise has gained significant industry traction through high-profile collaborations: * TV SD Concept Report: The company's algorithms have received a concept report from T?V S?D, validating the reliability and trust of the automated safety metrics. * Innotec (TV AUSTRIA Group): A strategic partnership that combines Paitron's automation with innotec's deep safety expertise to streamline workflows for global customers. * Intel Ignite: Modelwise was selected for the prestigious Intel Ignite deep-tech accelerator program, joining a select group of startups focused on industry-disrupting hardware and software.

Leadership and Corporate Structure

The company was founded by Florian Grigoleit (CEO), Arnold Bitner (CSO), and Iliya Valchev, who recognized the commercial potential of their research within the Model-Based Systems & Qualitative Reasoning group at TUM.

With a remote-first, globally distributed engineering team, Modelwise is backed by prominent venture capital firms, including Join Capital, Berkeley SkyDeck, and Emerging Ventures. As of 2026, the company continues to expand its AI capabilities, aiming to move beyond failure analysis into autonomous design optimization.