PRODUCTION AI, BUILT TO HOLD UP

Production AI for workflows that matter.

We turn stalled prototypes, messy operational data, and high-friction processes into AI systems your team can actually run.

Led by Javier Barrios  ·  AI platform architecture  ·  English & Spanish

FROM DEMO TO DEPENDABLE

PRODUCTION READY

01 · INPUT Data + workflow
02 · INTELLIGENCE Models + tools
03 · OPERATIONS Deploy + observe
OWNED BY YOUR TEAM Deployed  ·  Observable  ·  Documented
AGENTIC SYSTEMSContext, orchestration, tools
COMPUTER VISIONDetection, tracking, edge
DATA PIPELINESRetrieval, forecasting, insight
PRODUCTION DELIVERYDeployment, evals, monitoring

SELECTED WORK

Proof before promises.

Real client and research engagements, described at a non-confidential level.

CLIENT ENGAGEMENT

Westport Alpha

Equity-research workflow built for live earnings preparation

Built and deployed a workflow that reconciled market data across formats and frequencies, then automated valuation, short-interest, consensus, and earnings-preparation analysis.

  1. 01Company setupNormalize sources and reporting cadence
  2. 02ReconcileAlign market and financial data
  3. 03AnalyzeValuation, shorts, and consensus
  4. 04PrepareLive earnings workflow and reminders

RESEARCH SUPPORT

NLP research support for a Yale Law professor

Developed and refined a natural-language-processing framework that turned a large corpus of United Nations General Assembly resolutions into structured, research-ready results.

8,650+UN RESOLUTIONS STUDIED

WAYS TO WORK TOGETHER

Start where the risk is highest.

A defined workflow, a visible acceptance bar, and a handoff your team can keep using.

THE ACCEPTANCE BAR

“Done” means your team can run it.

A demo can impress. A production system has to survive ownership, failure, and change.

  1. 01DEPLOYED

    A reproducible path from repository to running system.

  2. 02OBSERVABLE

    Health, failures, and behavior are visible—not guessed.

  3. 03TESTED

    Critical output has checks against silent regression.

  4. 04DOCUMENTED

    Your team knows how it works and how to change it safely.

HOW IT WORKS

One workflow. Three clean decisions.

No sprawling discovery theater. We narrow the problem, make the system dependable, and transfer ownership.

  1. 01

    Scope

    Choose one workflow and define what “production-ready” means.

  2. 02

    Stabilize

    Fix the data, model, integration, evaluation, and operating gaps.

  3. 03

    Ship

    Deploy it, document it, and hand over a system your team owns.

ENGINEER-LED DELIVERY

AI systems usually fail at the seams—data, deployment, evaluation, and ownership. BarrNone is built around those seams.

Javier Barrios  ·  AI Platform Architect

SELECTED TECHNICAL DEPTH

  • Agentic systems + context engineering
  • YOLO / TensorRT computer vision
  • Python, FastAPI, React, Docker
  • GCP deployment + vector retrieval

BRING THE STUCK WORKFLOW

Let’s turn “almost working” into owned and operational.

A free 20-minute call is enough to decide whether the right next step is an audit, a rescue sprint, or no engagement at all.