Learning and memory
Xevrion remembers what happened, and gets better because of it.
Most software forgets. Xevrion keeps an ordered memory of your business and scores every forecast and recommendation against reality, then adjusts how far to trust itself.
Overview
Memory is an audited timeline of your organisation’s events, decisions and lessons. Learning is the loop that scores each forecast and recommendation against what really happened and adjusts future trust and confidence, within fixed limits.
Business memory
Typed, tagged events and decisions on one timeline.
The same customer everywhere
Records from every tool matched into one business model.
From its own track record
Forecast error and recommendation success change future behaviour.
How learning works
Four steps, repeated every cycle.
These are the actual rules the platform applies, with the thresholds written in.
Every forecast is scored
When the real numbers arrive, Xevrion lines them up with what it forecast for the same periods and measures the gap.
- Input
- The forecast, its range and the actual results
- Xevrion
- Average error (MAPE, with WAPE when actuals are zero), bias, tracking signal and how often reality fell inside the stated range
- Output
- A learning record with lessons, such as 'error above 25%: recalibrate' or 'ranges too narrow'
- You control
- Every learning record is visible to you
Every recommendation is scored
When a recommendation has been acted on, its real benefit and cost are compared with what was expected.
- Input
- Expected benefit, cost and confidence; actual benefit, cost and whether it succeeded
- Xevrion
- Benefit error, cost error, expected against actual return, and whether expectations were materially off
- Output
- A learning record and an updated status: successful or unsuccessful
- You control
- You record the outcome, or it is read from your tools
Models and rules adjust to their track record
Across the latest 500 learning records, Xevrion adjusts how much it trusts each forecast and how confident its recommendations should be.
- Input
- Forecast errors per measure and the recommendation success rate
- Xevrion
- Trust = 1 − average error (kept between 0.25 and 1). After 3+ misses above 25%, the forecast moves to an ensemble and is flagged. Confidence is scaled by success rate ÷ 70% (between 0.5 and 1.2)
- Output
- Updated model settings, recorded with the reason for each change
- You control
- Changes are recorded as their own learning record, with lessons you can read
What happened is kept, in order
Important events, decisions and lessons are stored as typed, tagged memories on a timeline for your organisation only.
- Input
- Events from every system: decisions, outcomes, changes, lessons
- Xevrion
- Stores each memory with its type, subject, time, data and tags, and audits every write
- Output
- A searchable history the next decision can draw on
- You control
- Memories are deleted with your data when you leave
In numbers
Error falls; trust follows.
In this example, a revenue forecast starts 31% out. Each cycle is scored and recalibrated, and the trust Xevrion places in it rises as the error comes down.
The rule
Trust multiplier = 1 − average error. At 31% error the forecast is trusted at 0.69; at 9% it is trusted at 0.91. Above 25% for three cycles, it would be switched to an ensemble and flagged for recalibration.
What it keeps
What Xevrion remembers, and for how long.
| Memory | What it holds | Kept | When it goes |
|---|---|---|---|
| Business memory | Events, decisions and lessons | For as long as you are a customer | Deleted when an owner completes deletion |
| Learning records | How forecasts and recommendations performed | For as long as you are a customer | Deleted with your organisation's data |
| Approved knowledge | Procedures and answers your team approved | Until it expires or is replaced | Expired items are flagged, never silently used |
| Financial records | Invoices and payments | As accounting rules require | Archived, then removed when the rules allow |
| Audit trail | Who did what, and when | Kept as evidence | A minimal record of deletion remains |
Everything in learning and memory
The capabilities behind it.
Data you can trust 5
- Data sources and syncConnect accounting, CRM and operational sources and keep them in sync.
- File ingestionBring in spreadsheets and exports when there is no connector.
- Source healthShows when each source last synced and whether it is healthy.
- Entity matchingJoins the same customer, product or supplier across sources into one business model.
- Data-quality auditFinds gaps, duplicates and inconsistencies, and tracks each one to resolution.
Decisions and learning 7
- Decision recordsWhat was decided, by whom and why, kept for review.
- Execution trackingFollows each decision through to what was actually done.
- Forecast vs realityEvery forecast is scored against what happened.
- Recommendation outcomesEvery recommendation is scored against its real benefit and cost.
- Self-improvementTrust in models and confidence in recommendations adjust to their track record.
- Business memoryA timeline of important events, decisions and lessons, kept per organisation.
- Decision qualityCalibration scores that show how far forecasts can be trusted.
Questions
About learning and memory.
Does Xevrion learn from other companies' data?
No. Learning happens inside your organisation only: your forecasts, your outcomes, your memory. Nothing is shared between customers, and your data is not used to train AI models.
Can learning make things worse?
Adjustments are bounded: forecast trust can never fall below 0.25 or rise above 1, and recommendation confidence is scaled between 0.5 and 1.2. Every change is recorded with its reason.
What happens to memory when we leave?
It is deleted with the rest of your organisation's data when an owner completes deletion. Only a minimal record that the deletion happened is kept.
How long before learning makes a difference?
It starts with the first matched forecast or recorded outcome. Some thresholds need a minimum number of observations, such as three forecasts or five recommendation outcomes, so one bad result cannot change behaviour on its own.
A platform that gets better with your business.
Start with one system; learning begins with the first measured result.
No sales calls Every price published Your tools, your permissions