Process Mining & Intelligence
Our process mining and process intelligence consulting starts from a simple fact: every process has two versions, the one in the documentation and the one in the event log. Process mining reconstructs the second — every case, every activity, every hand-off — from the systems that already record it, and shows where work stalls, loops or deviates from policy.
It applies wherever a process is high-volume and crosses systems and teams: customer onboarding, payment exceptions, claims, order-to-cash, procure-to-pay. The approach is always the same — connect to the systems that already record the process, deliver a working pilot on one process within weeks, then scale across products, regions and touch-points while monitoring continuously.
Offerings
Process discovery
Harmonise event logs across workflow, core and case-management systems into one case timeline; discover the real process map.
Bottleneck & rework analysis
Quantify where cases wait, loop and get reworked — by product, team, region and transaction type.
Conformance & compliance
Detect deviations from the designed process and control points from the log, not after the fact.
System + human touch-points
Cover the hand-offs between systems and people, where most delays and compliance gaps hide.
Continuous monitoring
Keep the discovered process live so improvements are measured and regressions are caught.
Improvement roadmap
Prioritised interventions grounded in measured performance — the input to automation, redesign or staffing decisions.
Where AI does the work
Discovery tells you what happened. The AI layer tells you why, what will happen next, and what to do about it — and increasingly does it.
- 01
Root cause, not just location
Machine-learning models on the case attributes explain why cases wait, loop or fail — by product, channel, team and time — instead of leaving analysts to guess from a bottleneck map.
- 02
Predictive process monitoring
Live cases are scored for the probability of breaching an SLA, missing a control or being reworked, so teams intervene while the case is still open.
- 03
Next-best-action recommendations
For each at-risk case the model proposes the intervention with the best measured outcome — escalate, re-route, pre-fill, wait — and learns from what worked.
- 04
Agentic remediation
Where the fix is routine and the control allows it, an agent performs it: re-requesting a document, re-assigning a queue, opening the ticket — with every action logged back into the event log.
Our approach
- 1
Connect
Extract event data from the source systems with default connectors; agree the case definition and activities.
- 2
Pilot in two weeks
Deliver a working process model on one product family or process — real data, real findings.
- 3
Scale
Extend across the full estate: every product, every region, every touch-point.
- 4
Improve & monitor
Quantify and prioritise the fixes, then monitor the process continuously as changes land.
Outcomes
What changes
- An objective view of where the process actually stalls, by product and by team.
- Compliance and hand-off failures detected from the log rather than reported after the fact.
- One evidence-based improvement roadmap instead of competing anecdotes.
- A repeatable method: the second process onboards far faster than the first.
Questions we're asked about process mining & intelligence
Fast. With event logs from your source systems and our default connectors, a first working pilot on a single business process is typically ready within two weeks.
Timestamps, case identifiers and activity names from the systems the process runs through — workflow, core banking, ERP, case management. We harmonise them into one event log.
High-volume, multi-system processes with hand-offs: customer onboarding, payment exceptions, order-to-cash, procure-to-pay, claims. If it has a case ID and timestamps, it can be mined.
No — it comes before it. Process mining shows what actually happens, so you automate the right process rather than the documented one.