Cortex AI
Agent workflow: assemble evidence, assist with drafting and coordination, and apply configured permissions, evaluation, approval, and monitoring controls.
Banking & FinanceGovernance & assurance
Investigators spend substantial time collecting transaction context and documenting their reasoning. Disconnected evidence creates repeated searches and inconsistent case preparation.
Solution blueprint: implementation is scoped with your team. The workflow below describes an engagement approach; it is not evidence of a completed customer deployment or a guaranteed return.
FROM PROBLEM TO PROCESS
Gather authorized transaction, account, and prior-case context.
Create a timeline and source-linked case summary for investigator review.
Track missing evidence, review actions, and the approved case disposition.
Genellipse maps the business rules and source systems, configures the agreed capabilities, and validates the workflow with the people who will operate it. Existing systems and supported interfaces determine the integration approach.
Agent workflow: assemble evidence, assist with drafting and coordination, and apply configured permissions, evaluation, approval, and monitoring controls.
Data foundation: connect approved sources, prepare governed datasets, track lineage and quality, and support repeatable analysis and reporting.
Assurance workflow: connect requirements, controls, owners, review tasks, and evidence so responsible specialists can assess and approve the work.
VALUE TO MEASURE
Increase investigative capacity by reducing evidence assembly time. Track substantive review quality and re-opened cases, rather than treat a lower alert count as proof of reduced risk.
Agree definitions, data sources, and an observation period before the MVP. Compare similar work, include exception handling and quality review, and subtract implementation and ongoing operating costs.
A current-state workflow map, data and interface assessment, configured MVP, evaluation evidence, and a phased delivery recommendation. Agree the output, acceptance criteria, operating owner, and improvement measures before extending the scope.
BUILD YOUR BUSINESS CASE
Replace these example assumptions with your own baseline and validated MVP results. This calculator estimates the value of processing-time improvements; it does not predict a customer outcome.
ILLUSTRATIVE FIRST YEAR
Released capacity becomes cash savings only when spending is actually avoided. Otherwise, measure the value of agreed redeployment or additional output. The realization percentage must reflect that distinction.
Annual hours = monthly volume × minutes saved per item × 12 ÷ 60. Annual realized value = annual hours × hourly cost × realization percentage. First-year cost = implementation cost + 12 × monthly operating cost.
First-year value ROI = (annual realized value − first-year cost) ÷ first-year cost. Payback = implementation cost ÷ monthly value after recurring costs, when that monthly value is positive.
The example assumes steady volume and immediate full operation. Include integration, licensing, AI usage, infrastructure, support, quality review, training, and change management in your costs. Model ramp-up separately before an investment decision. Currency selection changes the unit label; it does not convert amounts. Do not add the same benefit again as headcount savings, revenue, or avoided rework.
Tell us about your source systems, current bottleneck, and the outcome you want to measure. Your selected use case will be added to an editable enquiry so we can start with the right context.
Discuss this use case