You're pledging to donate if the project hits its minimum goal and gets approved. If not, your funds will be returned.
We are building what is closest to synthetic sentience in an open-source cognitive framework: Adam. Adam is an autonomous robotic prototype driven by a custom Python-based state machine. Currently, advanced real-time decision logic is locked behind closed corporate R&D and massive institutional labs. This project pulls complex cognitive loops out of abstract software and deploys them onto physical, localized edge-compute hardware. By giving a Python state machine a physical body, we are building a fully reproducible blueprint for independent creators to engineer enterprise-grade cognitive robotics outside of traditional academic channels.
The overarching goal is to engineer a fully functional, autonomous robotic unit that processes complex environmental stimuli natively—without cloud latency—and to open-source the entire codebase and hardware schematic.
I have already engineered the core Python software architecture for Adam’s sensory processing and state management. To achieve physical autonomy, I will build a localized edge-compute server cluster from surplus enterprise IT hardware, mount it to a mobile chassis, and integrate advanced LiDAR and ultrasonic sensor arrays. Adam's state machine will process this real-time environmental data to make autonomous physical navigational decisions.
The funding is strictly stage-gated. The minimum funding stands on its own as a complete experiment, ensuring the project ships even if the maximum goal is not reached. I am taking $0 in personal compensation.
The Minimum Funding ($1,500): The Physical Prototype. If we hit only the $1,500 minimum, I can successfully execute the core project: pulling the Python state machine out of the terminal. This funds:
$750 for the physical chassis, structural prototyping materials, and untethered servo mobility.
$350 for the sensory input arrays (LiDAR and ultrasonic) to feed physical data to the state machine.
$400 for a basic localized edge-compute board (e.g., Jetson Nano) to execute the Python logic onboard.
The Funding Goal ($10,000): The Enterprise Edge-Compute Cluster. The remaining $8,500 unlocks the full vision. It replaces the basic edge-compute board with a localized, rack-mounted server cluster. Utilizing my experience sourcing surplus government IT hardware, this funds the procurement of enterprise rack-mount controllers, switches, server power supplies, and high-capacity battery arrays. This allows the physical chassis to process heavy machine learning loops and NLP sentiment engines natively, completely eliminating compute bottlenecks and cloud latency.
I am Matthew Wringer, the solo developer and builder on this project. Formally, I am an Economics and Political Science double major, providing a strong foundation in systemic logic and state-based decision models. Technically, I am an independent quantitative developer with a track record of building automated financial trading algorithms and dynamic valuation models using Python, machine learning, and natural language processing.
I possess hands-on expertise bridging software with physical infrastructure, routinely sourcing and integrating surplus enterprise IT hardware and rackmount controllers through government surplus auctions. Furthermore, as the founder of an independent corporate entity, Vesper Industries LLC, I operate with the strict autonomy, capital efficiency, and structural discipline required to execute and document a highly technical hardware build.
The technical risks scale depending on the funding tier achieved:
At the $1,500 Minimum: The primary risk is compute bottlenecks. Forcing a basic edge-compute board to process dense LiDAR point clouds while managing real-time physical servo movements may result in software-to-hardware latency, limiting Adam's operational speed.
At the $10,000 Goal: The primary risk shifts to untethered power management. Engineering a high-capacity battery array to safely power enterprise rackmount servers alongside physical drive servos could face crippling voltage drops.
Outcome if it fails: The project is a net positive for the open-source community regardless of tier. Even if physical autonomy is compromised by latency or power constraints, the fully documented Python state-machine architecture and the localized hardware schematics will still be published open-source on GitHub, providing a foundational blueprint for future independent builders.
$0. The software architecture for Adam’s cognitive loops has been entirely bootstrapped and self-funded up to this point. I currently have pending applications with micro-grant organizations (including the 1517 Fund, The Awesome Foundation, and NLnet) strictly to cover physical chassis components and edge-compute hardware, but no external capital has been awarded or received yet.