Overview
Converse is Prizm’s AI-powered conversational interface that allows users to manage data assets, trigger workflows, generate recommendations, and explore the data catalog — all through natural language.
Powered by Claude (Anthropic) as the default model, Converse uses MCP (Model Context Protocol) tool integrations to autonomously invoke the right Prizm capabilities based on user intent.
How Converse Works
User Input (natural language)
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Intent Detection
(What does the user want to do?)
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Tool / MCP Selection
(Which Prizm capability handles this?)
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Execution + Context Gathering
(Searches catalog, lineage, profiling, org context)
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Recommendation Cards or Action Results
(Displayed as structured, actionable UI components)
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User Reviews → Approve / Reject / Create
What You Can Do in Converse
Data Discovery
"Show me all tables in the Finance domain that haven't been updated in 7 days"
"What are the most critical assets downstream of the customer_transactions table?"
"Find all assets tagged PII in the Marketing product"
"Generate descriptions for all tables in the sales schema"
"Update attribute descriptions for the orders table"
"Recommend business terms for the customer domain"
Quality Management
"Recommend quality metrics for the orders table"
"What data quality issues are open in the Finance domain?"
"Run a profile on the new_customers table"
Glossary & Governance
"Generate a glossary for the Customer360 domain"
"Create a business term for 'Customer Lifetime Value'"
"Recommend domains for the recently discovered assets"
Execution & Creation
Converse can directly trigger actions — not just recommend them:
| Action | Example Prompt |
|---|
| Create domain | ”Create a new domain called Logistics” |
| Create glossary terms | ”Add the recommended terms to the Finance glossary” |
| Run profile job | ”Profile the top 10 tables by usage in the Data Warehouse” |
| Run quality job | ”Run all completeness metrics on the orders table now” |
| Apply asset mappings | ”Apply the recommended domain mappings for the new assets” |
AI Model Configuration
Converse routes requests to the appropriate model based on task complexity:
| Task Type | Default Model | Rationale |
|---|
| Asset descriptions | Lightweight (Claude Haiku) | High volume, simple generation |
| Metric descriptions | Lightweight (Claude Haiku) | Templated output |
| Business Metric Recommendation | Advanced (Claude Sonnet/Opus) | Requires deep reasoning |
| Governance Recommendation | Advanced (Claude Sonnet/Opus) | Complex domain analysis |
| Glossary Generation | Advanced (Claude Sonnet/Opus) | Organization context synthesis |
| Conversational Q&A | Claude Sonnet | Balanced cost/capability |
Model selection is configurable by platform Admins under Settings → AI Configuration. Claude is the default for all Prizm AI operations.
Contextual Awareness
Converse uses the following sources to enrich its responses:
- Existing Domains — Current domain structure and ownership
- Existing Glossary — Business terms already defined in the catalog
- Asset Metadata — Descriptions, tags, profiling statistics, quality scores
- Organizational Summary — Company context and business vocabulary
- Lineage — Upstream and downstream asset relationships
- Usage Insights — Who uses what data and how frequently
Recommendation Cards
When Converse generates recommendations, they appear as structured cards in the chat:
┌─────────────────────────────────────────────────────┐
│ 🤖 Quality Metric Recommendation │
│ │
│ Asset: sales.orders │
│ Metric: Completeness — customer_id │
│ Confidence: 97% │
│ Rationale: customer_id is used in 23 downstream │
│ models and has historically maintained 99.8%+ │
│ completeness. A drop below 99% would impact │
│ revenue reporting. │
│ │
│ ✅ Approve ❌ Reject ⚙️ Customize │
└─────────────────────────────────────────────────────┘
Permissions
All Converse actions respect:
- Module licensing — Features available based on your Prizm license tier
- Mode configuration — Guided vs. autonomous execution modes
- User permissions — Role-based access controls (RBAC/ABAC)
A Member-role user will not be able to trigger metric creation even through natural language — permissions are always enforced at the execution layer.
Guided vs. Autonomous Mode
| Mode | Behavior |
|---|
| Guided | Converse presents recommendations and waits for user approval before any action |
| Autonomous | Converse executes approved action types automatically based on configured trust levels |
