Applied AI for operational decisions

Models for decisions that are expensive to get wrong.

Analytica builds predictive models and decision-support systems for government and enterprise teams. Our work includes utility storm forecasting, critical-infrastructure analysis, equipment-failure prediction, and workforce analytics, from first analysis through production deployment.

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founded: 2015
client-reported outage reduction: 15%
pipeline incidents analyzed: ~62,000
live public tools: 22

We have built for

CISA / U.S. Department of Homeland Security
JLL
Government of Alberta
Sharek Academy
Southern California Edison

§ 01

What we do

AI & Data Science Delivery

Predictive models, forecasting, and applied machine learning built on the data you already hold, with production deployment when the engagement calls for it.

Predictive and risk models across tabular, geospatial, text, and sensor data
Forecasting, anomaly detection, clustering, and recommendation systems
Model validation and explanation for operational, executive, and regulatory review
Production deployment on your infrastructure, when in scope, with documentation and monitoring

Training & Enablement

Live courses for analysts and decision-makers in the same room, with no programming background required.

AI for Decision Support in Defense Operations — 3 days
R for Data Science: Foundations of Analytics — 5 days
Custom cohorts assembled from a 16-topic curriculum
Worked exercises around real mission scenarios

Decision-Support Platforms

Maps, dashboards, alerts, and document-intelligence platforms that put model output in front of operators, program managers, and response teams.

Cloud-hosted GIS and analytics platforms
Dashboards built around operational filters and workflows
Automated data feeds and severe-event alerting
Reports written for the people who act on them

§ 02

Selected work

All work →

Energy · Utilities

2 years

Predicting where a storm will break the grid — five days out

A two-stage model that forecasts damage by district, then converts that into the crews and materials to pre-stage.

Southern California Edison

15%

client-reported outage reduction

Energy · Environment · Public sector

38 years of records

Four decades of pipeline incidents, and the gap between reporting and resolution

Roughly 62,000 incidents across 38 years. 94% were reported the same day; 20% were resolved the same day.

Government of Alberta

~62,000

incidents analyzed

Automotive · Telematics

19,000 km over 11 days

Telling drivers apart from the way they drive

Sensor telemetry from an 11-day, 19,000-kilometer expedition, reduced to a behavioral signature that identifies who is behind the wheel.

A global automotive manufacturer

78%

identification accuracy

§ 03 — products

Software we build under our own name.

22 applications are live — no signup; three are shown here. 7 are federal data tools built entirely from public records: federal spending data, FAA sighting reports, GAO and CRS papers, ship tracking.

Federal data toolsNetwork · map · time slider

Constellation

An interactive map of the US government’s Counter-UAS contracting network, drawn live from federal spending records — every node a real agency or firm, every line a real award. Shows where small and disadvantaged firms sit in Counter-UAS procurement.

Open Constellation

See all 22 products →

§ 04 — Founder

Dr. Aous Abdo

Aous is a physicist. He spent a decade in federally funded research — the Milagro observatory at Los Alamos, then a National Academy of Sciences fellowship on NASA’s Fermi mission, held across NASA and the Naval Research Laboratory — extracting faint signals from noisy instrument data and defending the results under expert review. He now applies the same methods to client work.

Figures from the INSPIRE-HEP author record.

INSPIRE-HEP ↗

Principal’s research record

peer-reviewed papers: 108
citations: 24,900+
h-index: 75
papers in Science: 9

“Working with Dr. Abdo was a real pleasure. His abilities to extract value from big data are first class. Creative thinking, attention to detail, and high personal standards ensured that we were successful in meeting our objectives. I hope to work again with Aous in the future.”

Adam Wilson · Global Product Director, JLL

A personal reference about Dr. Abdo from the JLL engagement, not a firm-level reference.

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Tell us what decision, workflow, or data problem you're working on. We'll tell you what the data you already have can support, and what a first engagement looks like.

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