Operations and finance. Chief Operating Officer
AI for the COO Office
Your operation runs on exceptions. Most of them wait in an inbox.
The standard process works. It’s everything that doesn’t fit that costs you. Cases stuck in shared inboxes, facts buried in PDFs, machines that fail without warning and partners who mark their own homework. We map the COO Office the way your operation actually runs, then put agents where the work gets stuck.
The short answer
It takes on the work that slows operations down. Agents triage and resolve exceptions, read documents no system can, predict equipment failures before they stop work, track partner SLAs from raw data and show where sites drift from the standard.
Your teams keep the judgment, the safety calls and the hard cases. The agents take the volume, so cost to serve falls and service gets more reliable.
The mandate
Run the business every day. Keep cost, quality and service in balance while the strategy changes around you.
What the board measures you on
Operating margin
And how it moves with volume
Cost to serve
Per order, case or customer
On time in full
By site, customer and lane
Capacity use
People, plants and assets
Quality and incidents
Defects, errors and safety
SLA attainment
Internal and partner
The canvas of the COO Office
Most operations AI automates the happy path. The money sits in the exceptions, the documents and the partners you rely on.
Canvas 1
What you run
The operation, every day.
Core operations
Production, service delivery or fulfilment, depending on the business.
Shared services
Back office processing centres, in house or outsourced.
Customer operations
Service centres and field service, often shared with the CX Office.
Assets and maintenance
Plants, fleets, equipment and the work orders that keep them running.
Logistics and fulfilment
With the Supply Chain Office.
Canvas 2
What you answer for
The things the CEO, customers and regulators hold you to.
Operating model
Standard processes and how work is split across sites and partners.
Operational risk and continuity
Business continuity, incident management and safety.
Outsourced delivery
BPOs, 3PLs and contract manufacturers and their real performance.
Agents in the operation
Which work agents do, where people step in and how it’s logged.
Where value leaks
None of them show up as a single big failure. They show up as queues, delays and a cost to serve that won’t come down.
01
Exceptions handled by hand
Every case that doesn’t fit lands in a shared inbox and waits.
Exception agents. Triage each case with full context and resolve it, route it or prepare it for a decision.
Touchless rate
Exception cycle time
02
Knowledge trapped in documents
Reports, emails, PDFs and forms that no system reads.
Document agents. Read, structure and link unstructured documents to your ERP and operational data.
Hours saved per case
Time to decision
03
Unplanned downtime
Equipment fails without warning and work stops.
Maintenance agents. Combine sensor data, work orders and technician notes to flag likely failures and raise the work order.
Unplanned downtime
Maintenance cost
04
Service backlog
Long queues, repeat requests and slow resolution.
Service agents. Resolve routine requests end to end, including the back office step.
Cost per case
Backlog age
05
Process variance between sites
The same process run ten different ways.
Process discovery agents. Map how work really flows from system logs and flag variance from the standard.
Process conformance
Cost per transaction
06
Partners marking their own homework
BPO and 3PL performance reported by the partner itself.
SLA agents. Measure partner performance from raw data and keep a ledger of credits due.
Partner SLA attainment
Credits recovered
Process lifecycles
We start from the systems you already run. The orange steps are where an agent takes on the work, so your teams spend their time on the cases that need them.
Issue to resolution
Every case and exception
Intake
From any channel or system
Agent
Triage
With full context
Agent
Resolve
Or route to the right person
Agent
Close
Root cause
Patterns across cases
Agent
Typical systems. ServiceNow, Salesforce Service Cloud, Genesys, shared inboxes
Maintain to operate
Every critical asset
Monitor
Sensors and logs
Agent
Predict
Likely failures flagged
Agent
Work order
Parts and history attached
Agent
Repair
Review
Typical systems. IBM Maximo, SAP PM, IoT platforms
Shared service processing
Every transaction
Request
Read
Forms and documents
Agent
Process
In your ERP
Agent
Quality check
Every item, not a sample
Agent
SLA report
Typical systems. ERP, workflow tools, document platforms, BPO platforms
Plan to deliver
With the Supply Chain Office
Demand plan
Supply plan
Schedule
Replanned on live signals
Agent
Fulfil
Deliver
Returns
Reasons read and grouped
Agent
Typical systems. SAP IBP, o9, Kinaxis, ERP, WMS, TMS
Agent intervention point
The COO control tower
Not a weekly ops review built from site reports. A live view of cost, service and backlog across sites and partners, with a brief on where the operation is stuck.
Illustrative
COO control tower
Sample data to show the view. Not client results.
Cost to serve
€18.40
▼ 9% per order
OTIF
93.4%
▼ 1.2 pts
Touchless rate
58%
▲ 17 pts
Over SLA
1,240
Open cases
Downtime
3.1%
▼ 1.4 pts
Partner SLAs met
91%
Site B at 82%
This week’s operations brief
Backlog
Address change exceptions up 40% after the system release
Root cause found in one validation rule. Fix proposed
Asset
Two packing lines show the same vibration pattern that came before last month’s failure
Work orders raised with parts reserved
Partner
3PL partner reports 97% on time. Raw scans show 89%
Credit claim of €36k drafted. SLA agent
Done
Supplier onboarding now completed end to end by agents
Cycle time down from 9 days to 2
Process conformance by site
Rotterdam
91%
Antwerp
84%
Dubai
76%
Lyon
58%
Lyon runs 14 extra manual steps in order handling. Cost per order 22% above the group average.
Illustrative example. Figures are invented to show how the view works. In discovery we build it on your own data and KPIs.
Your industry changes the agenda
The canvas stays the same. What the operation actually does all day does not. Here’s the question we hear most from operations leaders in each industry, and where agents help first.
CPG
How do we run more lines and co packers without adding overhead?
Exception handling and partner SLA tracking
FMCG
How do we keep plants running at high utilisation with fewer stops?
Predictive maintenance on critical lines
Retail
How do we run stores and fulfilment centres to one standard?
Process conformance across sites
D2C
How do we scale fulfilment and returns without the cost scaling too?
Returns and order exception agents
Automotive
How do we handle warranty and service claims faster and more fairly?
Claims document reading and decisions
Healthcare
How do we cut admin so clinical staff spend time on patients?
Referral, scheduling and document agents
Energy
How do we keep remote assets running with fewer site visits?
Asset monitoring and work order agents
Manufacturing
How do we close the gap between the best plant and the rest?
Process discovery and variance alerts
Logistics
How do we handle more shipments without more people in the office?
Booking, customs and exception agents
BFSI
How do we process claims and applications faster within the rules?
Document reading and case processing
B2B technology
How do we keep support and operations costs flat as customers grow?
Ticket resolution and internal operations agents
Proof
Less time to process insurance claims by reading unstructured documents alongside ERP data
Automotive insurer, GCC region. COO Office
Increase in warranty conversions
Automotive insurer, GCC region
How the COO Office connects
Operations turns plans and purchases into service, and every slip shows up in finance and with customers. The agents that serve the COO Office share the same platform and data as the offices around it, so a fix in one place holds across the relay.
How we’d start
Pilot 1
One exception queue, cleared
↳
Exception agents on your busiest shared inbox or queue
↳
Each case resolved, routed or prepared for a decision with full context
↳
Measured on touchless rate, cycle time and cost per case
Your decision
Which queues and sites to add next.
Pilot 2
One document heavy process
↳
Claims, maintenance reports, onboarding forms or customs files read by agents
↳
Facts linked to your ERP and operational data
↳
Run side by side with your current team for a month
Your decision
Whether document agents take on the full volume.
Both run under our Validation First Framework. They’re tested on your own data before you commit a larger budget, and if the numbers don’t hold, we tell you.
Your intervention map
Bring your largest backlog, your cost to serve and the site or partner that worries you most. We bring the COO Office canvas. In one session we map it to your systems and sites, and mark where agents would pay back first.
01
Your COO Office canvas
What you run and answer for, checked against how your sites, shared services and partners really work.
02
Your value chain
The canvas placed on your industry and your operating model, with the systems behind every case.
03
Your intervention points
Each leak with an agent design, its controls and the KPI it moves. Delivered as a mind map, an architecture view or an interactive dashboard.
AI for the COO Office, answered
What can AI do for the COO Office?
Agentic AI takes on the work that slows operations down. Agents triage and resolve exceptions, read documents no system can, predict equipment failures before they stop work, track partner SLAs from raw data and show where sites drift from the standard process. Cost to serve falls and service gets more reliable.
How can AI handle operational exceptions?
Exception agents read each case as it arrives, gather the context from your systems and documents, and either resolve it, route it to the right person or prepare it for a decision. Cases stop waiting in shared inboxes, and the patterns behind repeat exceptions become visible.
Can AI read unstructured documents like forms, reports and emails?
Yes. Document agents read PDFs, scanned forms, maintenance reports and emails, pull out the facts that matter and link them to your ERP and operational data. In one insurance operation, this cut claims processing time by 80%.
Can AI help with predictive maintenance?
Yes. Maintenance agents combine sensor data, work order history and technician notes to flag assets likely to fail, then raise a work order with the parts and history attached. Planned repairs replace unplanned stops.
Does this work with outsourced partners and BPOs?
Yes. Agents can track BPO, 3PL and contract manufacturer performance from raw data rather than partner reports, and they can work alongside partner teams on the same queues. You keep your partners and get a truer view of what they deliver.
Where should a COO start with agentic AI?
With one exception queue or one document heavy process. Both have clear volumes, costs and cycle times, so the result shows quickly in touchless rate, cycle time and cost per case.
