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, and workforce analytics, from first analysis through production deployment.
- founded
- 2015
- client-reported outage reduction
- 15%
- client organizations
- 9
- live public tools
- 20
- CISA / U.S. Department of Homeland Security
- JLL
- 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 either published course.
- 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
Federal · Critical infrastructure
Since 2018
Predicting how a hurricane cascades through US critical infrastructure
Record linkage across federal and commercial sources that share no identifier, then a forecast of how a storm moves through the assets it links.
CISA, as a subcontractor
5+
infrastructure sectors linked
§ 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 from public records — federal spending data, FAA sighting reports, GAO and CRS papers, ship tracking — or synthetic scenarios, never client data.
Federal data toolsFive markets · live federal spending data
Constellation
Five federal contracting markets — Counter-UAS, cybersecurity, AI and machine learning, space and satellite, and health IT — drawn live from federal spending records as agency, prime and subcontractor networks, with the small-business set-aside lanes broken out.
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 — Founder and 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.