01
AI Systems Architecture
Model selection, retrieval, evaluation, and the boundaries between them. The decisions that are expensive to reverse, made deliberately and before the code is written.
AI Architecture & Engineering
Assembled for the mission.
Dissolved when it’s done.
VEXIL designs and builds AI systems that run in production — architecture, agents, and internal tooling. Every project has a fixed scope, is built by the senior team that scoped it, and is handed over working. No junior staffing, no strategy decks.
- How it works
- Fixed-scope projects.
Agreed objective, agreed end date. - Who you work with
- The engineers who build it.
No account manager in between. - What you get
- Working software in production.
Documented and handed over.
Most AI consulting fails
before the first sprint.
The generic playbook arrives before anyone has understood the problem. A senior name sells the engagement and junior staff deliver it. What lands is a strategy deck, a proof of concept that never leaves the notebook, and a maintenance burden nobody inside the building can carry.
VEXIL runs the opposite way. A small senior team, embedded against a specific objective, doing the architecture and the engineering themselves. No translation layer between the people who scoped the work and the people who ship it — and no standing retainer once the objective is met.
Common failure modes
F-01Playbook precedes problem
F-02Sold senior, staffed junior
F-03Prototype with no path to production
F-04Handover that creates a dependency
F-05Retainer outlives the objective
What VEXIL builds
Five areas of work. Most projects combine two or three of them, and none of them get handed to someone else after the contract is signed.
02
Applied Agent Engineering
Tool design, orchestration, and failure handling for agents that run against real systems. Built to stay observable when they misbehave, because they will.
03
Rapid Prototyping
A working build in the hands of the people who asked for it, fast enough that their feedback still changes the outcome. Throwaway or foundation — decided up front, not discovered later.
04
Executive AI Tooling
Personal assistants and internal ops automation for people whose time is the binding constraint. Built around one person’s actual workflow rather than a product roadmap, and operated once it is live.
05
AI Strategy & Ops Advisory
Where AI belongs in the organization, what it costs to run once the pilot ends, and which of the current proposals should be killed. Direct answers, on the record.
Scope. Build.
Hand off. Close out.
Four phases with a defined end. You know what happens in each one, what you get at the end of it, and when the engagement closes.
Phase 01
Scope
Define the objective, map the systems it touches, and agree in writing what finished looks like. Days, not a discovery phase billed in months.
Phase 02
Build
Architecture and engineering in the open. Working software in review on a short cycle, with direct access to the people building it.
Phase 03
Hand Off
Documentation, runbooks, and a walkthrough with whoever owns it next. Nothing is engineered to require the team that built it.
Phase 04
Close Out
The engagement ends on the agreed date. Ongoing support is available if you want it, but it is opt-in and never assumed.
Selected deployments
Live systems, described without the parts that are under wraps. Detail available under NDA.
Executive AI Assistant
A personal AI assistant system for a senior media executive — correspondence, scheduling, research, and briefing prep running against live accounts with a human in the loop. Built and operated end to end.
Real-Time Tactical Mapping
A mapping platform for time-critical geospatial data: layer control, live feeds, and rendering tuned to stay legible under a single analyst’s attention rather than a dashboard committee’s.
Open-Source Intelligence Platform
Collection, verification, and mapping for open-source intelligence, built so provenance stays attached to every plotted claim instead of being lost at ingest.
Automated Content Pipeline
Raw source material to finished, scheduled output through an automated pipeline — with review gates placed where a human judgment call actually changes the result.
Client names withheld pending approval.
You work directly with
the people building it.
Zach Rice founded VEXIL Systems and leads the team. He builds production AI systems — real-time platforms, executive-facing tooling, and applied agent engineering — that run against live data rather than sitting in a deck.
Before moving fully into AI, he scaled a Web3 gaming community past a million members. That is where the second half of the toolkit comes from: distribution, audience, and a working understanding of how a product actually reaches the people it is for. He operates in public, with a substantial following across tech and AI.
Current work includes building and running a personal AI assistant system for a senior media executive — a live system with real organizational stakes, not a pilot. Architecture through deployment stays inside the team that scoped it, which is the point.
- Role
- CEO & Founder
- Domain
- Applied AI · agent systems · real-time platforms
- Track Record
- Multiple live production deployments
- Prior
- Scaled a Web3 gaming community past 1M members
- Presence
- Operates in public — large tech and AI following
- Scope
- Architecture → prototype → production, in house
Start a project
Describe what you need in a paragraph. If it is a fit, the reply comes from the team that would build it. If it is not, you get told that directly.
contact@vexilsystems.io