Applied AI for operational decisions
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.
We have built for
§ 01
01
Predictive models, record linkage, and forecasting built on the data you already hold, with production deployment when the engagement calls for it.
02
Live courses for analysts and decision-makers in the same room, with no programming background required.
03
Maps, dashboards, alerts, and document-intelligence platforms that put model output in front of operators, program managers, and response teams.
§ 02
Energy · Utilities
2 years
A two-stage model that forecasts damage by district, then converts that into the crews and materials to pre-stage.
Southern California Edison
15%
reduction in outage times
Energy · Environment · Public sector
38 years of records
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
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
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
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
Applied productsSHAP · NHANES reference · batch + API
Estimates diabetes, pre-diabetes, cardiovascular, hypertension, kidney and fatty-liver risk from measurements a routine physical already produces — then shows a SHAP attribution for every prediction, so you can see which inputs drive each estimate. Each input is placed against the NHANES population distribution.
Open GlucoGuard
Applied productsGeo-held-out CV · 49 states
Scores every US neighborhood against a brand’s existing store footprint and ranks the places that look like its best-performing sites but hold no store yet. Cross-validated by holding out whole states, so the model is judged on geography it has never seen. Built on public demographics, business mix and POI density.
Open Twinsite§ 04 — Founder
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.
Principal’s research record
“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.”
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.
