Mimasa AI vs BadMars
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Mimasa AI compared with BadMars
| Detail | 
Mimasa AI | 
BadMars |
|---|
| What it does | Enterprise agentic automation platform that unifies data, reasons with AI agents, and executes workflows across 180+ systems
| Fail here first.
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| Stage | Not given
| Startup
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| Founded | Not given
| 2026
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| Based in | IN
| RO
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| Pricing model | Not given
| Freemium
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| Pricing | Forever Free: $0/forever (5 credits/day, 1 user, 100MB storage). Standard: $29/month (120 credits/month, up to 5 users). Growth: $99/month (400 credits/month, up to 10 users). Business: $199/month (850 credits/month, up to 25 users). Enterprise: $499/month (2,100 credits/month, up to 100 users). Cus
| Not given
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| Key features | - Connect 180+ enterprise systems including ERPs, CRMs, databases, APIs and files
- Natural language data transformation and analysis
- No-code workflow builder for business teams
- AI agents with human-in-the-loop approvals
- Multi-step reasoning across long-running workflows
- Predictive forecasting with statistical models and machine learning
- Interactive dashboards and reports built from natural language
- Full data lineage and audit trails for governance
- On-premise or private cloud deployment options
- Role-based access control with encryption in transit and at rest
| - Panel of 12 hostile specialists trained to find different failure modes
- Verbatim anchoring of every finding to your document
- Score computed by formula based on failure severity and probability
- The Frog: identification of the one critical problem to fix first
- Debrief debate feature to argue back with evidence
- Available in Claude and ChatGPT
- Android app for mobile access
- Program tracking across multiple missions and frog history
- 48-hour full refund guarantee on first Landing
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| What makes it different | - Unified intelligence and execution layer - same system that reconciles data also carries out resulting actions
- Agentic reasoning adapts to exceptions instead of failing on them
- Self-operating workflows that improve as they handle more cases
- Model-agnostic platform supporting multiple LLMs and deployment options
- Deployment inside customer perimeter with data residency controls
| - Ranked findings with concrete next steps, not opinions
- Start free, upgrade after seeing results
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 27 ▼ −1 (down) since last check | 7 ● no change since last check |
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| Trust Flow (Majestic) | 20 | 2 |
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| Citation Flow (Majestic) | 20 | 15 |
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| Referring domains (Majestic) | 70 | 5 |
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4 details filled in for both companies.
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