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Mimasa AI vs Elpis

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 Elpis
DetailMimasa AI logo Mimasa AIElpis logo Elpis
What it doesEnterprise agentic automation platform that unifies data, reasons with AI agents, and executes workflows across 180+ systems Portable context for terminal coding agents
StageNot given Not given
FoundedNot given Not given
Based inIN Not given
Pricing modelNot given Open source
PricingForever 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
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
  • Context Ledger for curating admitted instructions, files and memory
  • Deterministic context admission before model processing
  • Workflows with Mother agent team design and checking
  • Love Spot drawing board with Matilda companion
  • Desktop app with theme customization
  • Support for GPT, Claude and Gemini models
  • Terminal and desktop app sharing state
  • Portable context for terminal coding agents
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
  • Deterministic context admission ensures agents see processed context before model receives it
  • Context Ledger provides transparent curation of agent inputs
  • Mother agent orchestrates multi-agent workflows with checking and merged results
  • Collaborative drawing interface with AI companion
Community votes00
DR (Domain Rating by Ahrefs)27 −1 (down) since last check7 no change since last check
Trust Flow (Majestic)200
Citation Flow (Majestic)2012
Referring domains (Majestic)706

3 details filled in for both companies.

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