One decision layer
across your business
Four suites, Enterprise Search and Data Governance. Twenty-six domain modules. Hundreds of applications, all built from the same four engines and deployed against the problems your teams already own.
Prediction, exception management and scenario planning underneath the planning tools your teams already use. From demand to fulfilment.
Predict the exposure, detect the drift, evidence every intervention. Nine domains from EHS to ESG, with the trail attached.
Reconciled plans, forecast drivers, margin bridges and close risk, computed continuously instead of assembled monthly.
Every deal and account scored on your own history, so the forecast carries its odds and at-risk accounts surface months early.
Ask in plain language across everything your business knows and act on a cited answer. Driven by Nexus, permission-faithful by design.
The whole corpus read against your policies, every breach owned, and governed agents cleaning the estate. Conformance as a measured number.
ML as a project vs. an operating capability
Only 5% of companies are future-built for AI and capturing value at scale. 60% get minimal or no material value. The difference is not the models. It is whether prediction runs as a capability.
| ML as a project | Prophesee: ML as a capability | |
|---|---|---|
| Time to an answer | Nine months per question | The same day |
| The models | One model, picked early | 62 models competing. Only the champion ships |
| The proof | A slide showing accuracy | Blind backtest and calibration curve, published with the model |
| After go-live | Nobody re-checks | Re-scored daily, challenged continuously |
| The team | A data science team per use case | The platform is the data scientist |
| The next question | Starts from zero | Ask it |
Eight weeks to proven value
A value evaluation, not a pilot: scoped on your data, measured against your baseline, handed over running.
Design
- Select the decisions that best validate the case
- Capture today's baseline to measure against
- Agree dates, owners and expected outcomes
Develop
- Connect the systems of record behind the decisions
- Configure the suite applications on your data
- Capture the rules that turn output into action
Deliver
- Validate results with end users against the baseline
- Prove the agreed metrics with the evidence attached
- Hand over the running system and plan the next modules
Put a decision layer under your function
Eight weeks, your data, your baseline. See it proven.