Runner Concepts · Prototype portfolio
Melissa capabilities, shaped into guided customer workflows.
Four connected product concepts show how data quality, audience intelligence, identity review, and AI-native operations can become clear, governed experiences.
Exploratory prototypes · readiness and connection state are labeled throughout
Shared workflow model
Human governed- 01UnderstandProfile the customer, records, and intended outcome.
- 02RecommendSurface the right Melissa capability and explain why.
- 03ApproveConfirm scope, cost, policy, and consequential actions.
- 04ExecuteRun through governed provider and system boundaries.
- 05ReviewPreserve results, exceptions, and an audit trail.
Product map
Three core workflows. One vertical exploration.
The products share foundations, but each begins with a distinct customer job. Select any card to see the experience and current proof.
Turn raw files into approved, executable data-quality plans.
Profile, diagnose, recommend, approve, run, and reconcile work through Melissa and Unison boundaries.
Build, verify, activate, and manage a trustworthy audience.
Audience Intelligence handles discovery and enrichment. CRM carries approved records into outreach, suppression, and learning.
Resolve identity discrepancies with explainable evidence.
Bring provider signals, record differences, review decisions, and escalation history into one operator workspace.
Apply the same governed foundations to institutional work.
An AI-native student information system concept for records, enrollment, advising, finance, and policy-controlled assistance.
Explore Melissa Campus →One important distinction
Audience Intelligence and CRM are different modules—not competing products.
Audience Intelligence owns discovery, territory, enrichment, and verification. CRM is the operating foundation for approved records, suppression, campaigns, provider jobs, credits, and audit history.
Primary product hypothesis
Data Quality Workbench
A governed workflow layer over Melissa and Unison execution.
The customer experience owns planning, approvals, progress, evidence, exception review, and receipts. Melissa and Unison remain the deterministic execution providers.
- DefineUpload and map customer data.
- DiagnoseProfile quality and explain the highest-impact findings.
- PlanRecommend a recipe, outputs, safeguards, and estimated scope.
- RunRequire approval before provider execution.
- ReviewReconcile results and preserve evidence.
Connected customer workflow
Audience Operations
One journey across discovery and activation.
Present this as a single solution with two launchable modules. Customers should understand where records come from, how they were verified, which policies removed them, and what happened after activation.
Territories, audience discovery, enrichment, verification, exports, and lawful-use controls.
Contacts, suppression, campaigns, communication, provider jobs, credits, and audit history.
Human-reviewed workflow
Verification Review
Explain discrepancies without overstating the decision.
The workspace organizes approved signals and lets an operator examine differences, record a bounded decision, and preserve an appeal or escalation path. It does not claim to be autonomous fraud decisioning.
- Signal reviewCompare record and provider evidence.
- Reason codesExplain why an item entered the queue.
- Human actionApprove, return, or escalate with notes.
- AuditPreserve who reviewed what and when.
Experimental vertical
Melissa Campus
A vertical demonstration of the shared foundations.
Campus shows how verified identity, governed records, model routing, human approvals, and operational audit can support a focused institutional system—not merely a generic chatbot.
Shared platform
Build common foundations once.
The public products remain focused because cross-product responsibilities live in an intentionally private platform layer.
Customer operations
Tenant context, contacts, suppression, provider policy, jobs, credits, campaign state, and audit.
Melissa capabilities
Verification, enrichment, identity, postal, matching, location, and licensed data services.
Governance
Approval gates, permissions, claim boundaries, evidence, exception review, and human accountability.
AI assistance
Explain, recommend, and prepare work while consequential actions remain deterministic and reviewable.
Prototype access
Launch the experiences that are currently hosted.
Access controls and legacy compatibility domains remain visible until each canonical deployment is migrated.
Canonical hosted deployment not established.
Canonical hosted deployment not established.
Truthful presentation
Show the work. Label the boundary.
These are Runner Concepts-custodied exploratory prototypes for the Runner EDQ–Melissa opportunity. They should be presented as evidence of possible workflows, not as commissioned, production-ready, or officially adopted Melissa products unless that status is documented.