| What it does | Enterprise agentic automation platform that unifies data, reasons with AI agents, and executes workflows across 180+ systems
| AI-native forward deployed engineering software for enterprise customer deployments
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| Stage | Not given
| Startup
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| Founded | Not given
| 2025
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| Based in | IN
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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
| Free during launch for all plans. Developer: $0/month (1 customer, 2 environments). Startup: $249/month or $2,988/year (10 customers, 25 environments). Growth: $849/month or $10,188/year (75 customers, 150 environments). Enterprise: Custom pricing. If using Meetext's AI model, charged on usage at ap
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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
| - Supports 14 enterprise destinations including Slack, Teams, ChatGPT, Claude, Salesforce, ServiceNow, HubSpot, Notion, Linear, Atlassian, Asana, Google Chat, Cursor and VS Code
- Personal data masking and usage budgets with kill switch
- Health checks, incident response and three-layer monitoring
- Customer-written acceptance criteria that rerun on each publish
- Hosted MCP endpoints and customer installation portals
- Cross-customer gap detection and pull request generation
- Permission-aware AI agent that requests confirmation before acting
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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
| - Automates the repeatable deployment work that scales linearly with customer count, avoiding the need to hire more forward deployed engineers
- Priced per customer environment rather than by API traffic or usage volume
- Verifies changes only when customer-written acceptance criteria pass, not just when code is deployed
- Includes AI agent for common operational tasks but all changes require human confirmation
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 27 ▼ −1 (down) since last check | 7 ▲ +4 (up) since last check |
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| Trust Flow (Majestic) | 20 | 1 |
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| Citation Flow (Majestic) | 20 | 20 |
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| Referring domains (Majestic) | 70 | 7 |
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Mimasa AI
Meetext