An Independent Supply Chain Lab
Peakview Labs designs and builds AI systems for supply chain operations. Five working prototypes and one full platform, each taken from problem framing through to running code.
Why It Exists
Supply chain problems that are obvious at the operating level rarely get solved in software. The people who understand them do not build, and the people who build have not run an operation. Peakview Labs closes that gap from the operations side: the problems come from twenty years of running supply chains, and the systems get built rather than specified.
How It Works
One person, with AI carrying the implementation. Problem framing and architecture stay human; the model writes most of the code. That is what makes it possible to take a system from a blank page to working software without a delivery team.
Problems from the operating floor, answered in working code
Background and Technology
Two decades of supply chain leadership and an MIT MEng in Supply Chain Management, with systems built on AWS and designed to connect to the enterprise platforms supply chains already run on.
How a System Gets Built
A Problem Worth Solving
Every system starts from a failure mode seen first-hand in an operation, not from a feature list.
Framing & Architecture
The problem gets modelled and the architecture decided before any code exists. This part stays human.
AI-Assisted Build
The model carries the implementation work, which is what compresses the build cycle.
Running Software
The output is working code, not a specification or a slide deck.
Honest Assessment
What the system handles well and where it breaks both get written down.
What Peakview Labs Is
Operator-Led
The problems come from twenty years running supply chains at Amazon, CVS Health, and Clean Harbors. The same person who framed them built the systems.
Working Software
Five prototypes and one full platform, all running code. Each one does the job it was built to do.
AI Where It Earns It
AI carries the implementation work and the document understanding. Where a deterministic rule is the right answer, the system uses a deterministic rule.
Domain First
Supply chain judgement is the scarce input. Writing the code is the easy part now; knowing which problem is worth solving is not.
How This Is Different
A lab rather than an agency. The difference shows up in what actually gets produced.
Problems From the Operating Floor
Every system on this site targets a failure mode seen while running an operation, not one inferred from a market report.
Built, Not Specified
The deliverable is running code. Design work exists to reach a working system, not to become the product itself.
One Person, End to End
Problem framing, architecture, and implementation sit with the same person, so nothing is lost in a handoff between a consultant and a developer.
Real Stacks, Named
Every prototype lists what it was actually built on, down to the runtime, the models, and the datastore.
Narrow on Purpose
Inventory, capacity, cold chain, remittance, and supplier risk. Depth in one domain beats breadth across many.
Full Code Ownership
Anything built under Forge transfers outright. No black boxes and no vendor lock-in.
What That Adds Up To
systems built end to end
in supply chain leadership roles
built solo, framing through to code
in efficiencies, earned in operator roles
Want to look at any of it more closely?
Happy to walk through how any of these systems works, what it took to build, and where it falls short.