HOW THE WORK ACTUALLY GETS DONE
The DSIE Framework — four phases, one accountable operator.
DIAGNOSE
Map every workflow in your operation. Identify exactly which processes are costing you money and estimate the value of targeted AI deployment. You receive a written report detailed enough to implement without us — because the deliverable earns its price whether or not you hire us next.
STRATEGIZE
Rank opportunities by ROI. Design the architecture. Define what the AI is allowed to touch, what requires human approval, and what the security layer looks like. Scope is locked before a line of code is written.
INTEGRATE
Build the spine first. Add one verified feature at a time. Every customer-facing and price-bearing action requires human confirmation. Every system is instrumented from day one — cost and performance are always visible, never a surprise.
EXECUTE
Operate, monitor, optimize. Your system runs in your accounts under your name. I maintain it, update it, and improve it monthly. You are never locked in — but I'm there to make sure nothing breaks quietly.
Most AI consultants deliver a recommendation to a team you don't have. Most managed AI services require your staff to build and configure the tools themselves. The DSIE Codex builds the system, secures it against real attack vectors, and operates it month to month. No internal technical team required.
FORCED TO WORK WHERE IT SHOULDN'T
The methodology behind every client deployment was first proven by forcing quantized language models onto a Snapdragon ARM laptop that Microsoft's own tooling refused to support — bypassing a RAM ceiling, injecting a runtime the OS actively blocked, and building a working eight-agent orchestration system on hardware it was never supposed to run on. The same builds that would be straightforward on supported client hardware took weeks of adversarial engineering on a machine the platform fought the entire time. If the methodology survives that constraint, your modern business hardware is a routine deployment.