Making vehicle repair faster and more predictable
Otter Work is an AI decision layer that diagnoses vehicles and predicts the spare parts a repair will need — before the truck reaches the workshop bay. Higher technician efficiency, higher throughput, less downtime.
Built for independent truck workshops and multi-location service networks across Europe.
Repair time is lost between diagnosis and parts availability
Workshops lose hours because parts are only sourced after diagnostics — while the bay and the technician sit blocked.
Ordered too late
Parts are ordered only after diagnostics are complete, so the wait starts when the truck is already on the lift.
Fragmented inventory
Stock is scattered across local warehouses, group stock and suppliers — with no single view of what is available when.
Manual search
Staff hunt across DMS, OEM portals, catalogs, email and phone calls to find and confirm the right part.
Active repair is only one part of the cycle
Two steps — parts search/order and parts wait — are where avoidable time hides.
The two highlighted steps are avoidable waiting. A day of truck downtime runs ≈ €500 — the pain that pays for prediction.
Breakdown → return to service
Check-in → release
Time in a productive bay
Active technician work
Measurement distinctions that matter. The 15% shop-turnaround-time improvement is a pilot hypothesis drawn from smartphone-repair workshop experience — not a Europe-wide audited benchmark — to be validated on timestamp-level data, with shop TAT reported separately from fleet downtime, bay occupancy and technician wrench time.
An AI decision layer on top of the systems you already run
The AI does the heavy lifting; the human stays in control at the business-rule gate — and every finished repair feeds the model.
Capture
Vehicle, mileage, symptoms, DTCs and repair history — from phone, email or intake.
Predict
Likely required parts with confidence scores, normalised across manufacturers.
Check
Local, group and supplier availability with ABC-class lead times.
Reserve
Reserve or pre-order parts under defined business rules — human-approved.
Prepare
Stage the parts before the truck reaches the productive repair bay.
Learn
Learn from actual diagnosis and repair outcomes to sharpen the next prediction.
One connected workflow, from repair order to prepared parts
Digital repair-order intake
Structured capture of VIN, symptoms and history — even from a phone call.
Predictive parts recommendation
Confidence-scored part predictions from the prediction engine.
Inventory & supplier visibility
Local, group and supplier stock in a single availability view.
Reservation & procurement
Reserve, advance-order or find alternative sourcing under business rules.
Bay scheduling & staging
Schedule the bay and stage parts so work starts without a wait.
KPI dashboard & APIs
Operational metrics plus integration APIs into existing systems.
The workshop floor, end to end
From the service order board to the technician bay, parts availability and purchasing — one connected system.
An AI copilot that does the parts busywork — you keep the final say
Otter Work doesn't just show you the plan. Conversational agents build the replenishment plan, draft the purchase orders and receive stock — and every money-moving action waits for a human tap to approve.
Replenishment copilot
Ask for a demand- or usage-based plan for the location, get the key SKUs and total spend summarised, then have it draft purchase orders grouped by vendor — reviewed and released by you.
Purchase-order copilot
List, place and receive purchase orders by reference in plain language. Placing an order with the supplier and receiving it into stock are one message away — each confirmed before it is written.
Drafts, never autonomous spend
Every write is an explicit approval, never a silent purchase. Receiving ledgers each stock movement, so the next usage-based forecast only gets sharper.
Open by default — built to fit the systems you already run
No rip-and-replace. Otter Work sits on top of your DMS, telematics and back office — and you choose how deep to connect, from a simple CSV to a live, two-way API. Start where you are today, upgrade whenever it suits you.
Start with CSV & spreadsheets
No IT project and no developers. Bulk-import your catalog, stock levels and part substitutions from a spreadsheet, and export replenishment plans and accounting to CSV for the tools you already run. The right fit for shops on legacy or offline systems.
Go live with the API & webhooks
When you are ready for real time, the same data flows both ways over a tenant-scoped API — telematics faults raise leads on their own, and every status change is pushed straight to your systems. Same platform, no migration; flip it on whenever it suits you.
Inside the live connection
Work flows in on its own
A DTC fault from a connected truck becomes a service lead automatically — with the odometer kept current so preventive-maintenance scheduling stays accurate. Every intake channel lands on the same board.
One API key, three query styles
A single tenant-scoped key unlocks the same data — orders, catalog, stock, purchase orders, vehicles and substitutions — however your integration prefers to read and write it.
- REST — full read/write CRUD for booking, catalog and stock sync
- OData — queryable feeds straight into Power BI, Excel & reporting
- GraphQL — shaped, nested queries for custom apps and dashboards
- Documented with OpenAPI, an interactive explorer, and self-serve keys you can revoke anytime
Events flow back out
Register a webhook and Otter Work POSTs a JSON event the moment a service order changes status — so your DMS, ERP, accounting and notification tools stay in sync in real time.
Authoritative European parts data (TecDoc / TecAlliance) and packaged DMS, ERP and telematics connectors are on the roadmap. Today you connect through CSV or the open API above — the pipeline is built to drop these in as they land, with no change to how you work.
Less waiting, more capacity, better predictability
Illustrative four-bay workshop, 90–100 repair orders a month — a value hypothesis for pilot validation.
90–100
Typical four-bay workshop
15%
Bay & technician time
12–15
≈ €450 contribution each
€5.4k–6.75k
Higher throughput & reliability
These figures are a value hypothesis for pilot validation, not a guaranteed outcome — the 15% utilization uplift is drawn from smartphone-repair workshop experience and will be validated on timestamp-level data. Actual impact depends on repair mix, current utilization, parts availability, and the workshop's ability to convert released capacity into additional work.
Faster repairs are just the start
The same data that stages parts on time also grows the top line, keeps trucks moving when a part is short, and scales from a single shop to a whole network.
Turn maintenance-due trucks into booked work
Otter Work watches every enrolled vehicle's mileage and time since last service and flags the ones due — one click turns them into leads on the order board. Fill the bays you would otherwise leave empty.
Never stuck on a single part
When the primary SKU is short, the availability engine offers interchangeable substitutes automatically — so one out-of-stock line doesn't leave a truck sitting on the lift.
One shop or a whole group
Stock, bays, orders and purchasing are location-aware, with shared items spanning sites — run a single workshop or a multi-location network on one platform, with group-wide visibility.
The intelligence layer between fleet and workshop systems
Not another system of record — a predictive operating layer that makes existing systems more useful. And the advantage compounds into a data flywheel.
Simple pricing aligned with workshop size
Additional revenue: implementation and data preparation (€1,500–5,000 per workshop) · custom integrations · premium SLA and support · group-level analytics and benchmarking.
Otter Work makes repair faster, more predictable, and easier to scale
We are validating predictive parts availability in live workshops — reducing avoidable waiting, improving bay throughput, and building a scalable B2B SaaS platform for Europe's repair ecosystem.