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Execlenz

The portfolio

Four platforms. One question, answered from both ends.

BizCase and Userz work top down, from what the business is trying to achieve. DataLenz and Tokenz work bottom up, from what you actually hold and run. Buy one, or run them together.

Business — top down

Start from what the business is trying to achieve, and work down to what to build.

BizCase

Find, cost and prioritise every AI opportunity

“Where do we invest in AI, in what order, and what comes back?”

Board, CFO, COO, CIO, CMO, CPO
Userz

Roll out AI to people, safely and measurably

“How do we get staff using AI without losing control of it?”

End users, operations, IT, HR

Technical & data — bottom up

Start from what you actually hold and run, and work up to what it can support.

DataLenz

Know whether your data can carry AI

“Is our data good enough to build on, and what will it expose?”

CIO, CDO, data stewards
Tokenz

Control what AI actually costs to run

“What are we spending on AI, where is it going, and is it worth it?”

CFO, finance and AI administrators

Side by side

The full comparison

Every platform assessed on the same fifteen dimensions.

Comparison of the four Execlenz platforms across audience, purpose, business focus, outcome, dashboards, readiness check, discovery area, ROI values, output, governance, AI capability, analytics, knowledge, compliance and primary value.
DimensionBizCaseUserzDataLenzTokenz
AudienceBoard, CFO, COO, CIO, CMO, CPOEnd users, operations, IT, HRCIO, CDO, data stewardsCFO, finance and AI administrators
Primary purposeDiscover, assess and prioritise AI and automation opportunities across the enterpriseDrive AI adoption, governance and enablementGovern and visualise enterprise dataGovern usage and cost of enterprise LLM consumption
Business focusStrategic measurement of investment, ROI, timing and FTE impactAI adoption, training and governanceUplift data for AI, automation and insightsAI operational cost management
Business outcomeBoard-ready business casesSuccessful user AI rolloutTrusted, AI-ready dataOptimised AI spend, monitored
Executive dashboardsReal timeReal timeReal timeReal time
Readiness checkFive-pillar maturity assessmentProgramme rollout plan, communications, audit and RACIData health, risk, security and governanceLLM baseline, areas for optimisation, savings
Discovery areaAll departments, all requirementsUser programme trackingData schema discoveryAI token usage discovery
ROI valuesCost savings, FTE impact, time to benefit, first-to-market proofs of conceptAdoption metricsData visibility and accuracyCost optimisation
OutputDetailed project plan with proofs of concept builtEnd-to-end user governanceEnterprise-wide visibility, risk and cost controlReal-time costs and trends by department and model
GovernanceInvestment, risk, impact and timingPolicy and complianceData and PII, auditLLM governance
AI capabilityRecommendationsPrompt libraryData insightsUsage assistant
Analytics & insightsLive business cases, maintained continuouslyTraining and adoption statisticsLineage analyticsUsage, spending and audit
KnowledgeSingle repository and source of truthPolicies, prompt library and training materialsData dictionaryAudit and consumption trends
ComplianceEvidence and approval gatesNIST AI RMFPIIAudit controls
Primary valueWhere to invest in AI and automation, with the ROI, risk reduction and competitive advantage quantifiedDeploy AI safely, attain the benefits, control how it is usedUnderstand the value of your data before committing AI spendControl consumption across AI platforms continually, and keep optimising spend against value

Scroll horizontally to compare all four.

See them running.

All four platforms have live demonstration environments, populated with representative data.

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