One graph. Every effectivity answer, with 100% certainty.
A multi-fleet operator's maintenance data lived in four different systems that barely spoke to each other. We connected all of it — engineering orders, illustrated parts catalogue, aircraft data and compliance records — into a single graph model: Maintenance Space.
Maintenance Space is a graph model of your entire maintenance world
Engineering orders, illustrated parts catalogue data, aircraft data and maintenance compliance data — normally scattered across systems that don't talk to each other — modelled as a single connected graph, not a warehouse of disconnected tables.
Aircraft effectivity, 100% certain
Effectivity is computed directly from the graph's own structure, not inferred from incomplete records — so the answer is certain, not a best guess.
Part numbers classified by fleet
Every part number is classified by fleet automatically, feeding straight into better demand forecasting and optimised inventory levels.
Master data validated across ERP
The graph cross-checks master data against every connected system, catching and correcting inconsistencies before they reach planning.
Procurement, improved via preferred vendors
Clean, effectivity-certain part data lets procurement route sourcing to preferred vendors with confidence, not workarounds.
Engineering orders, effectivity, and parts — connected, not siloed
Effectivity sits at the centre of the graph, connected upward to every engineering order that touches it and downward to every part number it governs — so an effectivity question can be answered by walking the graph, not reconciling spreadsheets.
| Part numbers | Engineering order | IPC chapter | Aircraft config |
|---|---|---|---|
| 1P2, 1P3, 1P20, 1P33, 1P76, 1P103 | EO_000231 | 25-11-99 | EC-AAA |
| 1P1, 1P2, 1P3, 1P4, 1P20, 1P33, 1P99 | EO_000133 | 52-13-99 | EC-AAA |
| 1P1, 1P3, 1P20, 1P33, 1P76, 1P99 | EO_000307 | 52-13-99 | EC-AAA |
| 1P1, 1P2, 1P3, 1P4, 1P20, 1P99 | EO_000222 | 30-10-00 | EC-BBB |
| 1P1, 1P2, 1P3, 1P4, 1P33, 1P76, 1P202 | EO_000167 | 33-20-10 | EC-BBB |
| 1P1, 1P3, 1P4, 1P20, 1P33, 1P76, 1P99 | EO_000189 | 25-11-99 | EC-CCC |
| 1P1, 1P2, 1P3, 1P4, 1P20, 1P33, 1P76, 1P231 | EO_000257 | 52-13-99 | EC-CCC |
| 1P1, 1P2, 1P3, 1P4, 1P20, 1P33, 1P76, 1P123 | EO_000154 | 52-13-99 | EC-CCC |
| 1P1, 1P2, 1P3, 1P4, 1P20, 1P33, 1P76, 1P145 | EO_000236 | 52-13-99 | EC-CCC |
| 1P1, 1P2, 1P4, 1P20, 1P33, 1P76, 1P167 | EO_000240 | 33-10-10 | EC-CCC |
| 1P1, 1P3, 1P20, 1P33, 1P76 | EO_000390 | 33-20-10 | EC-CCC |
| 1P1, 1P2, 1P4, 1P20, 1P33, 1P176 | EO_000173 | 33-20-10 | EC-CCC |
| 1P2, 1P3, 1P4, 1P20, 1P33, 1P78 | EO_000135 | 75-19-99 | EC-DDD |
| 1P1, 1P2, 1P3, 1P33, 1P76, 1P999 | EO_000279 | 30-10-00 | EC-DDD |
| 1P1, 1P2, 1P3, 1P76, 1P92, 1P4, 1P20 | EO_000109 | 33-20-10 | EC-DDD |
Every decision, grounded in data and facts
Alongside the graph sits an explorer built for high-dimensional data — a way to see across every domain at once, not one system at a time. It runs several layers of automated tests across the data in the client's ERP system, detecting and correcting deviations as they appear, so the model's accuracy compounds rather than decays.
The same graph that finds today's errors can predict tomorrow's needs
A validated, effectivity-certain graph is also a predictive one. Once the model trusts its own data, it can be extended forward — the specific prediction depends entirely on what the client needs next.
Predictive effectivity
Forecast which future engineering orders are likely to apply to which aircraft, before they're issued.
Predictive fleet demand
Project part-number demand by fleet ahead of the forecasting cycle, sharpening inventory decisions.
Predictive data risk
Flag records likely to drift out of sync across ERP systems before the deviation actually occurs.
Predictive vendor sourcing
Anticipate which preferred vendor best matches upcoming demand, by part, by fleet, by lead time.
How we build your Maintenance Space
The same five-stage build, whether the graph starts with two data sources or twenty.
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We ingest your data.
Engineering orders, IPC, aircraft records and compliance data, connected into a single graph model — no manual reconciliation required.
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We resolve effectivity with certainty.
Aircraft effectivity is calculated directly from the graph, not inferred — giving a 100% certain answer for every part number.
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We validate your master data.
Automated tests run continuously across your ERP systems, flagging and correcting deviations as they appear.
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We classify and forecast by fleet.
Part numbers are classified by fleet, feeding directly into better demand forecasting and optimised inventory.
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We turn the graph predictive.
The same model that validates today's data can be extended to predict tomorrow's — tailored to your specific decision needs.