Agents for aftersales and service operations
The technician carries the knowledge in their head. The back office carries the routine by hand. The records live in spreadsheets. Plovr puts AI agents on top of the systems you already run, one routine at a time, so the work gets done the same way every day, whoever is on shift.
Sound familiar?
Two places where service organisations lose time every day. Not because people are slow, but because the knowledge and the routine sit with people instead of systems.
In the field
Asset history in one system, bulletins in another, the fault described in an email. The answer is somewhere in a 600-page service bulletin that nobody can search from a van. The colleague who knows it by heart is retiring next year. So the first visit is a diagnosis and the second one is the fix.
In the back office
Status checks, claim matching, partner follow-ups: rule-bound work that has to happen every day and happens differently depending on who does it. Performance rises and falls with individuals, and when one of them leaves, the routine leaves with them.
Both problems have the same shape: the process runs through people because no system owns it. That is what the agents take over.
How it works
Every engagement starts with one of three problems. For each one you see what hurts today, what the agent does about it, and what you can measure afterwards.
Field service enablement
The problem
The technician arrives on site and starts by searching: the answer sits on page 412 of a bulletin nobody can search from a van, and the colleague who knew it by heart is retiring.
What Plovr does
Before the technician leaves, an agent assembles the asset history, prior faults, applicable bulletins and the parts kit into one briefing. On site, the technician asks in plain language and gets the answer from your own manuals and service history. The knowledge moves from heads into a system that new colleagues can use from day one.
What gets better
Back-office enablement
The problem
Status checks, claim matching and partner follow-ups happen every day, differently depending on who does them, and they leave with the person who did.
What Plovr does
An agent runs the routine every day, across every system it touches, and reports only the exceptions. Your team steps in when a decision is needed, not to do the checking. The routine runs the same way whoever is on shift, and it keeps running when someone leaves.
What gets better
System of record
The problem
Orders, serial numbers and shipments live in spreadsheets and mailboxes: nobody can say with certainty which unit went where, and an audit takes days to prepare.
What Plovr does
Plovr keeps the records that no existing system owns — including orders, serial numbers, and transports — in one place, where they are queryable, reportable, and exportable. Existing systems remain the source of truth for the records they already own; Plovr connects the data across them. These records form the data foundation for our agents and are built for medical traceability and the Digital Product Passport.
What gets better
Agents run on your cadence, not office hours
Hosted and processed in the EU, GDPR-compliant by design
Data migration. Your systems stay the source of truth
Every read and write logged, per agent, per run
Which routine is eating your week?
Stories · in production
Packwise runs Plovr as the system of record on top of Packwise flow, its own device management platform, and its finance and service systems. Plovr tracks every order, every serial-numbered unit and every transport in one place, and every unit has its own page with its full history.
What the agents take over
Each recurring routine becomes one agent: scoped, deployed and operating on its own. Nothing is sold as a suite. You start with the routine that costs you the most time and add the next one on the same rails. One routine can use several sub-agents underneath; you still deal with one agent and one result.
| Agent | What it does | Tasks managed by the team |
|---|---|---|
| Service intake & resolution | ||
| Service request intake | Turns call transcripts and voice messages into structured service requests, capturing the issue, customer, asset and relevant context. Flags missing or ambiguous information for human review. | Clarifying ambiguous requests with the customer |
| Technical support | Answers product and fault questions from your manuals, service bulletins and repair history — for technicians, dealers or even end customers. | Questions without precedent in the history |
| RMA intake & validation | Checks serial number, installed base and warranty entitlement, creates the return, issues the label and confirms to the requester in one pass. | Goodwill and out-of-warranty exceptions |
| Service execution | ||
| Repair quote & approval | Builds the quote from fault code, labour catalogue and parts, sends it, chases the approval and releases the job the moment it lands. | Pricing exceptions above threshold |
| Parts availability & shortage escalation | Checks required parts across available inventory and locations, identifies shortages and triggers the next action. Escalates prioritization, substitution or allocation decisions when needed. | Prioritisation, substitution and allocation decisions |
| Inventory reconciliation | Reconciles inventory records across systems and locations, identifies discrepancies and prepares corrections. Flags material or ambiguous discrepancies for human review. | Approving material corrections |
| Service control | ||
| Operational network follow-ups | Monitors open service jobs and automatically follows up when actions or information are overdue. Escalates cases that require intervention or partner management. | Approving the message, steering the relationship |
| Consumption trend triggers | Detects changes and anomalies in parts and service consumption and triggers the appropriate workflow. Surfaces emerging issues before they become operational problems. | Deciding which signal needs action |
| Scorecard watch | Monitors service performance and cost-to-serve against targets and highlights deviations and emerging trends. Brings the right issues to human attention. | Deciding what to do about it |
| Technical root cause analysis | Connects service and repair data to identify recurring failure patterns and potential root causes. Surfaces evidence and hypotheses for engineering or service teams to validate. | Confirming the root cause and the fix |
| Master-data cleaning | Detects incomplete, inconsistent or duplicate master data across connected systems and proposes corrections. Routes ambiguous or high-impact changes for review. | Approving high-impact changes |
Scroll the table sideways for all three columns
Not on the list? The rails are the same. If a routine of yours is recurring, rule-bound and spans more than one system, it is a candidate. We scope it before we quote it. Get in touch →
Rollout
No platform programme. The first routine goes live on its own, is measured against your own handling, and the next one follows on the same rails.
We connect to the systems you already run: ERP, CRM, field service, partner portals, carrier systems and parts catalogues, or the documents and spreadsheets the work actually lives in. Nothing is migrated, nothing is replaced.
Your rules, your process, your workflow: service commitments, escalation rules, who approves what. They become explicit logic, the fixed rails the agent runs on.
One routine goes live first. It shadow-runs against your team’s own handling, then switches to autonomous with human approval on the actions that commit money or dates.
We measure what changed for you: time per job, hours saved, error rate, first-time-fix rate. Then we tune the routine and add the next one.
Why teams trust it
Right now the routine runs the way each person happens to run it, and the handover is a folder and a wish. A Plovr agent runs the same path every time: the AI works inside defined steps, and its output is fixed in shape.
The Plovr approach
One path per process, deterministic where determinism is free, AI only where judgement is genuinely needed. Predictable output, predictable cost, and a log for every action taken in your systems.
Who builds this
Book a demo
We’ll walk through it against your actual systems and tell you honestly whether an agent is the right answer — and what it would take. 30 minutes, no deck required.
FAQ
Yes. Before the technician leaves, the agent assembles the asset history, prior faults, applicable service bulletins and the parts kit into one briefing. On site, the technician asks in plain language and gets the answer from your own manuals and service history, including the ones that run to hundreds of pages. What we measure afterwards: first-time-fix rate, jobs per day and time per job.
The recurring, rule-bound work that spans more than one system: status chasing and SLA monitoring, RMA intake and entitlement checks, warranty claim matching, parts availability and reservation, partner follow-up on open jobs, repair quoting and approval chasing, and scheduled performance reporting. The agent runs the routine every day and reports only the exceptions. What stays with your team: pricing exceptions, goodwill decisions, partner negotiation and anything where the right answer depends on a relationship.
Yes, where no system owns the record today. Plovr keeps orders, serial numbers and transports in one place, queryable, reportable and exportable, with every unit on its own page and its full history. Everything that already has a home system stays there. This is also the data basis the field-service and back-office agents work on, and it is the setup that is running at Packwise today.
No. Plovr sits on top of the systems you already run and leaves them as the source of truth. It reads and writes through the access those systems already offer. There is no data migration project, and no system in your landscape has to change its roadmap for Plovr to go live.
Hosting and processing are in the EU and the deployment is GDPR-compliant by design. Your data is never used to train foundation models. Access follows the permissions of the service account in each connected system, and every action an agent performs is logged and auditable.
By not letting the AI choose the route. Each process runs on one fixed path. The AI is used only inside defined steps, such as reading a partner email, classifying a fault or drafting a message, and its output is fixed in shape. Actions that commit money or a date require human approval, and every read and write is logged per agent and per run. Before an agent runs on its own, it shadow-runs against your team’s own handling.
We are early stage and are defining the final pricing model together with our first customers. It is a mixture of fixed and volume-based components, and we will make sure you get a sensible return on investment.
Plovr is designed to map specific workflows onto standard building blocks. During the initial configuration we define those settings together with you — and the second step of the implementation routine is exactly this: modelling your business and your workflows into agent-driven automation.
Yes. Packwise runs Plovr as its system of record on top of Packwise flow, its own device management platform, and its finance and service systems: every order, serial-numbered unit and transport is tracked in one place, and every unit has its own page with its full history. The story is on this site. The field-service and back-office agents run on the same rails.