Avantagram vs ModelRefs
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Avantagram compared with ModelRefs
| Detail | 
Avantagram | M
ModelRefs |
|---|
| What it does | Make the unknown measurable
| The AI Reference Layer for Implementation Decisions
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| Stage | Not given
| Not given
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| Founded | Not given
| Not given
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| Based in | IN
| US
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| Pricing model | Paid
| Freemium
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| Pricing | Starter: $29/month (3 workspaces, 4 analysis credits/month) or $290/year; Professional: $79/month (10 workspaces, 12 analysis credits/month) or $790/year; Agency: $199/month (custom workspaces, 30 analysis credits/month) or $1,990/year; Enterprise: Custom pricing with tailored commercial agreement.
| Free tier: 1,000 API calls per month. Starter: $19/month. Pro: $49/month. Business: $199/month. Builder: $19/month with 1,000 task executions. Scale: $49/month with 5,000 task executions.
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| Key features | - First-party website crawler and business profile extraction
- Deterministic 0-100 AI visibility scoring
- Brand mention and sentiment detection
- Competitor discovery and verification
- Source evidence and claim verification diagnostics
- Citation opportunity research and outreach lists
- Market-specific context isolation
- Live-Web Research and LLM-Only analysis modes
- Multi-workspace and multi-client isolation
- Actionable recommendations and content briefs
| - Evidence API with citations and governed benchmark runs
- Knowledge Graph connecting models, providers, benchmarks and workflows
- Rate limiting and monthly API allowances
- MCP server for agent integration
- Bearer token authentication
- Reference profiles and implementation context
- Status and methodology visibility for evidence gaps
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| What makes it different | - Evidence kept separate from visibility scores
- Measures only what AI can actually observe, not third-party verification
- Uses own first-party crawler, not external AI bot metrics
- Deterministic scoring from stored executions, not inflated AI estimates
- Recommendations grounded in measured telemetry, not guaranteed outcomes
| - Every benchmark score includes methodology limitations and claim scope so evidence cannot be presented without context
- Connected reference system organizing AI knowledge fragmented across announcements, docs and research
- All tiers access the same evidence base; differences are only in call volume and support
- Governance-aware methodology for compliance and risk review
- Free read access to all tutorial, reference and comparison content
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | Not checked yet ● no change since last check | 1 ● no change since last check |
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| Trust Flow (Majestic) | 0 | 2 |
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| Citation Flow (Majestic) | 0 | 17 |
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| Referring domains (Majestic) | 0 | 11 |
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6 details filled in for both companies.
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