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.
- founded
- 2015
- client-reported outage reduction
- 15%
- pipeline incidents analyzed
- ~62,000
- live public tools
- 20
- CISA / U.S. Department of Homeland Security
- JLL
- Government of Alberta
- Sharek Academy
- Southern California Edison
§ 01
What we do
01
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
02
Training & Enablement
Live courses for analysts and decision-makers in the same room, with no programming prerequisite on the decision-support courses.
- 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
03
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
SectorsGovernment & defenseHealthcareMiddle East & GulfCapabilities statement for federal buyers →
§ 02
Selected 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.
20 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
Federal data tools56 programs
Drift
Major defense acquisition programs, and the distance between what they were promised to cost and what they cost now. 56 verified programs, $1.3T baselined against $1.7T estimated, from GAO, CRS and DoD sources.
Open Drift
Applied productsLive demo, no signup
FlightRisk
Attrition risk with the explanation attached. Open it with a one-click demo persona — CHRO, VP or manager — and see the whole thing without an account.
Open FlightRisk§ 04 — The team
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.
He delivers alongside Dr. Amine Chouicha, chief technical officer, and Jacob Weiss, principal AI engineer. The practitioner who scopes an engagement stays with it through delivery. Meet the team →
Figures from the INSPIRE-HEP author record: 100 refereed publications of 109 indexed, retrieved 25 September 2026.
Principal’s research record
- refereed papers
- 100
- citations
- 24,900+
- h-index
- 74
- papers in Science
- 8
“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.”
A personal reference about Dr. Abdo from the JLL engagement, not a firm-level reference.
Discuss a project
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.