WedoLow provides an automated platform that analyzes embedded C/C++ code and generates optimized, production-ready versions tailored to specific hardware. The platform uses static and dynamic scans to identify performance bottlenecks, then leverages an MCP server connected to AI agents to apply expert-guided optimization techniques. It targets industries like automotive, aerospace, and robotics where execution time, energy use, and system reliability are critical constraints.
Funding
Funding not disclosed
Founders
Product
Problem
Embedded software development for constrained hardware requires manual, time-consuming optimization to meet strict performance, energy, and reliability requirements. Engineering teams often lack the tooling to systematically identify bottlenecks and generate code that is fully adapted to their specific hardware, leading to suboptimal execution times and increased power consumption.
Solution
WedoLow automates the analysis and optimization of embedded C/C++ code through a platform that combines static and dynamic scanning with AI-driven code generation. The platform first maps application structure and uncovers performance bottlenecks, then quantifies optimization opportunities in terms of CPU load, execution time, and memory usage. Through an MCP server connected to AI agents, WedoLow automatically triggers analysis, applies expert-guided optimization techniques, and generates production-ready code tailored to the target hardware. This enables engineering teams to improve software performance on constrained systems without compromising reliability or requiring extensive manual effort.
Target Audience
Primary customers are engineering teams in automotive, aerospace and defense, and robotics sectors that develop embedded software for constrained hardware and require optimized performance, energy efficiency, and system reliability.
Features
- Static and dynamic code analysis to uncover bottlenecks and map application complexity
- Quantified optimization opportunities with measurable unit gains in CPU load, execution time, and memory
- MCP server integration with AI agents for automated analysis triggering and code generation
- Expert-guided optimization techniques applied to generate production-ready C/C++ code
- Hardware-specific code adaptation for constrained embedded platforms
- Focus on industries with strict performance, energy, and reliability demands, including ADAS, real-time ECUs, avionics, and robotics