Forecasting · Classification · Dashboards

Forecasts and decisions your team can check, built on your own data.

We build forecasting, classification and anomaly-detection models on your operational data, back-test them against a simple baseline, and put the results into the dashboards and decisions your team already uses.

Diagnose this workflow →Book a fit call

Start: Workflow Diagnostic · from $7,500
Build: 4–8 weeks · from $25,000
Run: From $2,500/mo

Sound familiar?

Planning runs on last year’s spreadsheet and gut feel.
Reports describe what happened, not what is coming.
Models get built once and nobody checks whether they still work.

Where it applies

Demand and volume forecasting
Risk and anomaly detection
Customer and product segmentation
Executive and program dashboards

How it works

Four steps. One audit trail.

Clean cases flow straight through. Anything that does not match waits for a named reviewer, and every step is written to the log.

Clean cases flow straight throughExceptions wait for a named reviewerEvery step is logged

Explore
Profile the data, find the signal and document the gaps.
Model
Forecasting, classification and clustering, from ARIMA and Prophet to ensembles.
Validate
Back-test against a simple baseline before anyone relies on it.
Deploy
Dashboards and scheduled scores, monitored for drift.

Reconcile the records before the report is released.

Match operational and finance records using stable identifiers, isolate exceptions, and prepare a traceable reporting output.

Scenario

01Read extracts
02Reconcile keys
03Review decision
04Prepare report

Input & evidence

Operations extract · three records

JOB-201 · $1,200
JOB-202 · $2,400
JOB-203 · $800

Finance extract

JOB-201 · $1,200
JOB-202 · $2,400
JOB-203 · not present

Validation & review

Inspect the source, then run the checks.

Follow a case from input to a reviewed output. Try the exception and the matching scenario.

Ready to run

Every action is written to the decision trail.

Decision trail

Sample loaded. No external systems connected.

Prepared output

Nothing is released until the case passes validation and a reviewer approves it.

Fictional data and scripted outcomes that explain the design. Not a live SI system or a client result. See the connected reporting offer →

Controls built in

Every model back-tested against a baseline
Assumptions and limits documented in plain language
Drift monitoring once in production

What you receive

Validated model and feature pipeline
Back-test report against baseline
Dashboard or scheduled scoring output
Model card and handoff

Related proof

Leadership experienceFortune 10 healthcare distributor · Healthcare distribution

An item-matching redesign tied to $80M in added revenue.

$80Madded revenue

Challenge: High-volume product records had to be matched consistently, and manual review could not keep pace with the business.
Built: A redesigned matching process that applied deterministic rules first, model reasoning second, and routed uncertain matches to people.
Result: $80M in added revenue attributed to the redesigned process.

Rules + MLHuman reviewEvaluation

See the related offer →

OptiSyn engagementA specialty construction firm · Construction · Small business

Three disconnected systems became one live P&L in 21 days.

21days to deliver

10+hrs/week of entry eliminated

19governed data views

~$21per month to run

Challenge: Job costs, accounting entries and project spreadsheets lived in three places. Someone re-keyed numbers every week, and the owners saw profit by job only after month-end.
Built: SovereignOS: connectors to three source systems, 19 governed BigQuery views as a single source of truth, and a live P&L and operations dashboard on top.
Result: More than ten hours a week of manual entry eliminated. A live P&L by job. Running cost of roughly $21 a month.

BigQuerySharePointAccounting APIDashboards

See the related offer →