What happened?
- Envelopment analysis
- Benchmarking
- Reconciliation
TransformDecisionAnalytics
Rotenix designs complex decision-making pipelines and hands you the simple answer.
1
Operations research
Optimization, envelopment analysis, stochastic programming
2
Decision analytics spectrum
Descriptive · Diagnostic · Forecasting · Prescriptive
3
Local language models
On your infrastructure. Your data never leaves it.
Chapter 1 · The problem
Data-driven decisionsare no longer optional.
Yet for most organizations the path from raw data to actionable insight stays frustratingly complicated. Not because the answer is unknowable, but because everything between the question and the answer has been left in the way.
1
The data problem
Platforms that ask for a warehouse before they will answer a question.
2
The translation problem
Models whose reasoning survives only inside the team that built them.
3
The last-mile problem
Dashboards that describe the past and stop short of the decision.
Chapter 2 · The craft
Rotenix has masteredthe art of making thecomplex simple.
Behind every elegant interface and every straightforward insight sits a sophisticated engine. The simplicity is the product. The sophistication is the reason it holds.
1
Advanced operations research
Linear and mixed-integer programming, data envelopment analysis, stochastic and robust optimization. Chosen per problem, not per fashion.
2
The full decision analytics spectrum
Descriptive, diagnostic, forecasting and prescriptive stages composed into one pipeline, so an answer always carries the evidence behind it.
3
Cutting-edge local language models
Models that run on your infrastructure and turn a solved program into language a decision-maker can act on, without your data leaving the building.
4
Composed into decision pipelines
The layers above are not a menu. Rotenix designs the pipeline: which methods, in which order, against the data that actually exists.
An analytics engine that doesn't just process data. It provides decision advantage.
Chapter 3 · The spectrum
Four questions,one pipeline.
Most platforms stop after the first question. A decision needs all four, connected, so the answer at the end can point back to the evidence at the start.
1
Descriptive
What happened?
Performance reconstructed from the data that already exists: reconciled, comparable, and honest about what it does not cover.
- Envelopment analysis
- Benchmarking
- Reconciliation
2
Diagnostic
Why did it happen?
Contributions separated from coincidences. The pipeline decomposes an outcome into the drivers that actually moved it, and sizes each one.
- Decomposition
- Slack analysis
- Causal structure
3
Forecasting
What will happen?
Futures with their uncertainty attached. A forecast that hides its own error bars is a decision waiting to go wrong.
- Stochastic models
- Scenario generation
- Interval forecasts
4
Prescriptive
What should we do?
The decision itself: the feasible move that best serves the objective, with the binding constraint named so the trade-off is visible.
- LP / MILP
- Robust optimization
- Policy search
Chapter 4 · The reach
One solution for alldecision-making challenges.
The domains differ. The grammar of the decision does not. Rotenix brings a unified approach to understanding performance, and to improving it.
The decision
“Where will the next disruption cost you most?”
Network flow and robust optimization over the suppliers, lanes and buffers you already track, surfacing the handful of nodes whose failure actually propagates.
DescriptiveDiagnosticForecastingPrescriptive
Chapter 5 · The method
Minimal data in.Maximum insight out.
Traditional platforms demand extensive historical datasets and perfect information before they will say anything useful. Rotenix pipelines work with the data you already have, because the right method extracts more from a small, honest dataset than the wrong method extracts from a large one.
4
Analytics stages
composed per problem
10
Decision domains
one engine
1
Unified pipeline
end to end
Each point is a decision-making unit. The curve is the best performance actually observed, not a target invented in a workshop. What the pipeline returns is the shortest defensible path from where a unit is to where the evidence says it could be.
Chapter 6 · The output
Abstract mathematics,translated into a move.
Rotenix turns formal models into clear business intelligence, simplifying the act of deciding without sacrificing analytical rigour.
Output 1
Clear visualization of efficiency frontiers
Every unit plotted against the peers it is genuinely comparable to, with the frontier drawn and the distance to it made legible at a glance.
Output 2
Context-aware recommendations from efficiency patterns
Not a dashboard of metrics but a ranked set of moves, each carrying the constraint it respects and the improvement it is expected to buy.
Reallocate lane B → D92
Shift 14% of peak load71
Re-sequence batch 754
Hold current plan21
Output 3
Intuitive representation of complex relationships
The dependencies between decision elements shown as structure, so the reason behind a recommendation is inspectable, not asserted.
Transform decision analytics
Bring us the decisionyou keep postponing.
Tell us the question and what data exists today. We will tell you which pipeline answers it, and what it would take to stand that pipeline up.