What it is

A continuous measurement of usable capacity per pack, corrected for temperature and rest, and rolled up per vehicle, per site and per fleet. The measurement is derived from full-cycle behaviour the pack shows during normal operation, so it does not need a workshop test to update.

The number is exposed through the platform and the API. There is no electric vehicle where you can see this today.

What problem it solves, and for whom

Planners work off nameplate. Nameplate drifts down 3–8% a year, and no one adjusts. The result is a plan that quietly stops working — the missed stop, the shortened route, the vehicle that returns short.

For an operator selling capacity to a customer under an SLA, the gap between nameplate and delivered is a conversation nobody wants to have without data on the table.

The business case

Planning against measured capacity removes defensive padding and unlocks whole vehicles of daily throughput. For SLA-backed operations it also protects revenue: a documented delivered capacity is a defensible answer, not a negotiation.

What it is

A per-vehicle estimate that updates as conditions change. It combines measured capacity and internal resistance from the battery analytics with the planned route, the payload, ambient temperature and the driving profile the vehicle has shown on similar runs.

The output is a range in kilometres and a confidence band around it, available in the platform and through the API, so it can feed the planning system that decides the day.

What problem it solves, and for whom

Planners cannot use a nameplate range, so they pad. Padding shows up as an extra charge stop that was not needed, a route split across two vehicles that one could have covered, or a driver who returns early because nobody could tell them what the battery still had in it.

For fleet operators the cost is capacity that is bought and not used. For the people scheduling the work it is a daily negotiation with a number they do not trust.

The business case

Tighter estimates mean fewer defensive charge stops and more work per vehicle per day. Over a procurement cycle it also changes what gets bought: knowing what the current fleet genuinely manages is the difference between specifying the battery you need and specifying the one that makes the worry go away.

What it is

A charging policy that reads state of health, temperature and cycle history per pack and turns them into the instruction the charger receives: the target state of charge, the rate it is reached at, and how long the pack is left sitting full before it is used.

It runs on the chargers and battery management systems already installed. What changes is the instruction, not the hardware, so a site can move from a single overnight rule to per-pack charging without any work on the asset itself.

What problem it solves, and for whom

Most fleets charge everything to full overnight because it is the simplest rule to operate. It is also the most expensive one for the battery: a pack held at one hundred percent in a warm depot ages measurably faster than one charged to what the next day’s route actually needs.

Charge point operators see the mirror image. A site tuned for throughput pushes high rates into packs that are already warm, and the cost of that lands on someone else’s asset until it comes back as a warranty argument nobody has the data to settle.

The business case

The direct effect is slower degradation: less time at high state of charge, fewer high-rate sessions into warm packs, and rest periods that suit the pack rather than the shift pattern. On a fleet that replaces batteries on condition rather than on schedule, that moves the replacement point out by whole quarters.

The second effect is evidential. Every session is recorded against the pack, so the way a battery has been treated becomes something you can show a lessor, an insurer or a warranty desk instead of something you assert.

What it is

A control layer that measures how each pack behaves at the edges of its operating window and lifts the ceiling on state of charge, depth of discharge and cell voltage when the measurement supports it. The limit is per pack, not per fleet, and it moves as the pack ages.

It runs above the battery management system rather than replacing it: the BMS still holds the hard safety cut-outs.

What problem it solves, and for whom

Manufacturers set one conservative window for every pack in the fleet, so a pack that could deliver 850 is capped at 800 because the worst pack in the population needs the margin.

For storage operators the missing 50 kWh is capacity that was paid for and never used. For fleet operators it is a daily run that has to be planned around a limit that does not reflect the pack in front of them.

The business case

A 5–7% lift in usable energy across a site is common. On a 1 MW site that is a full extra hour of discharge, without touching the hardware or the safety envelope the BMS enforces.

What it is

A scheduling layer over the chargers on site. It takes departure times and planned routes, the site power ceiling, the tariff windows and the state of health of every pack, and produces a charging plan that satisfies all of them at once.

It runs continuously rather than once a night, so a late return, a failed charger or a changed route is absorbed by the plan instead of breaking it.

What problem it solves, and for whom

Most depots charge everything the moment it is plugged in, which puts the whole fleet on the grid connection at the same hour and at the most expensive rate of the day. The usual answer is to apply for more power, which is slow where it is possible at all.

For depot operators the immediate cost is peak demand charges. The slower cost is degradation, because the vehicles that need the gentlest treatment are charged exactly like the ones that do not.

The business case

Spreading the same energy across the available hours cuts the peak the site is billed on, and in a good number of depots it removes the case for a grid upgrade entirely. The second gain is that health constraints are part of the plan rather than an exception to it, so the fleet ages more evenly and replacement can be scheduled instead of discovered.

What it is

A standard report generated per pack, per vehicle or per site. It states measured capacity against nameplate, temperature exposure, cycle count and depth, charging behaviour, and every fault the battery management system has recorded, each with the date it happened.

Reports run on a schedule or on request, and come out as a PDF for people and as data for systems. The same record sits behind both, so the number in a handover pack and the number in your own dashboard cannot drift apart.

What problem it solves, and for whom

At the end of a contract, the condition of a battery is usually asserted rather than shown. Whoever is holding the asset at that moment carries the doubt, and doubt is priced.

Leasing companies see it as a discount at handover. Fleet owners see it as a resale price below what the vehicle is worth. Service providers see it as an argument about whether a pack was mistreated, with nothing on the table but opinions.

The business case

A documented history moves residual value from an assumption to a measurement, and it shortens remarketing because the buyer does not have to price in the unknown. It also keeps warranty claims viable: a claim supported by a temperature and cycle record is a different conversation from one supported by a service note.

What it is

A model of normal behaviour built per pack from its own operating history, and per population from the packs running the same duty beside it. Cell voltage spread, temperature gradient across the enclosure, resting behaviour and charge acceptance are each tracked against that baseline.

What comes out is a ranked list rather than a stream of alarms: which asset has moved, how far, how quickly, and what usually follows a movement of that shape.

What problem it solves, and for whom

A battery management system is built to protect the pack in the moment. It raises a fault when a threshold is crossed, which is late by design — the drift that led there has usually been visible for months.

For an operator that lateness is an unplanned intervention, often a full replacement where a module swap would have done. For a service provider maintaining sites under an availability agreement, it is a penalty for downtime that a month of warning would have prevented.

The business case

Work moves from unplanned to planned, which is where most of the saving sits: a scheduled module swap during a quiet window costs a fraction of an emergency call-out and the lost availability around it.

It also protects the warranty position. A divergence documented from the month it started is the difference between a supported claim and an argument about whether the pack was operated correctly.

What it is

An advisory engine that runs against imbalance markets, day-ahead prices, tariff windows and site power ceilings. It is aware of state of health, so a pack under health guidance is not scheduled into a stressful pattern.

Actions leave the platform as signals to the energy partner who executes the trade. The record of what was proposed, what was accepted and what was cleared sits with the pack it ran through.

What problem it solves, and for whom

A battery that is left idle between shifts is capacity that is bought and unused. The revenue that shifting the same energy across the right hour of the day would generate is measurable, and most operators never see it.

The pricing gap is that every cycle wears the pack. Trades that ignore that wear look profitable until the replacement comes due.

The business case

Signalled correctly, imbalance revenue is measurable in tens of thousands of euros per MW per year on grid-scale sites, before day-ahead is added. Priced against wear, the trades that clear are the ones that pay after the battery is replaced.

What it is

Session-level metering, a tariff engine and outbound integrations to accounting and ERP. Fuel and charge card links are supported natively. Roaming is handled through OCPI for charging and the equivalent formats for swap events.

The record on which the transaction settles is the same record the platform uses for analytics, so there is one source of truth for both operations and finance.

What problem it solves, and for whom

Session reconciliation between the meter, the CPO back office, the roaming hub and the fleet system is manual on most sites. Disputes without session-level data get resolved in the customer’s favour by default.

For swap stations, the settlement problem is bigger: the pack circulating through the fleet does not belong to the vehicle it powers, and the accounting has to reflect that.

The business case

Automated settlement removes the reconciliation work and closes the leak on unbilled sessions. On the roaming side, defensible session data unlocks revenue from partners that would otherwise write it off in disputes.

What it is

A mobile app for drivers and operators. It shows measured range for the current route and load, the queue of charging or swap sessions ahead, and a score with practical tips on the charging habits that are shortening or extending the life of the pack the driver is using.

The same data the platform runs on is the data the driver sees, so the number in the depot and the number in the cab match.

What problem it solves, and for whom

Drivers do not trust the range figure on the dashboard, because it was set when the pack was new. The reaction is defensive: an extra stop, a shortened route, a vehicle returned early.

Charging behaviour is the biggest single lever a fleet manager has over how fast the pack ages, and it sits in the hands of the person who was never told which of their habits mattered.

The business case

Trusted range figures reduce defensive stops and recover one to two runs per vehicle per week on typical urban duty. Behaviour nudges typically move a fleet’s average score fifteen to twenty points in a quarter, and that shows up in the aging curve.