Mira
Decentralized AI verification network for checking and validating AI outputs across models and autonomous systems.
Mira Verify and Mira Network focus on multi-model verification, claim checking, and trust infrastructure intended to reduce hallucinations and increase reliability of AI outputs.
Positioning
Verification layer for autonomous AI outputs
Key facts
- HQ location
- Singapore / San Francisco, CA, USA (public sources vary)
- Founded
- 2024
- Employee range
- 11-50 (11-50)
- Funding stage
- Seed
- Company type
- Private (Private)
- Pricing model
- Usage Based (API / usage-based; details not publicly disclosed)
- Last updated
- Jun 21, 2026
Revenue estimate
Unknown
Valuation estimate
Undisclosed
Investments
$9M seed round in Jul 2024 led by BITKRAFT Ventures and Framework Ventures
Target customers
AI application builders, autonomous AI developers, Web3/AI ecosystems, and teams needing output assurance
Key competitors
Patronus AI, Galileo, Braintrust, Arize AI, Fiddler AI, LangSmith, Vijil
Known customers
Ecosystem apps such as Klok publicly referenced; enterprise customers not broadly disclosed
Classification (raw research text)
- Core focus
- AI output verification and trust layer
- Core industry
- AI Infrastructure / AI Quality
- Core category
- AI verification platform
Shown verbatim from the research spreadsheet — deriving structured segment/industry tags from this text is a future phase.
Attribute breakdown
- AI Workflows Secondary feature
- Multi-agent Orchestration / Runtime Secondary feature
- System / API Integration Secondary feature
- Retrieval-Augmented Generation Secondary feature
- AI Quality Assurance / LLM Evaluation Primary focus
- AI Observability / Monitoring Secondary feature
- AI Security / Guardrails Secondary feature
- AI Governance / Policy Management Secondary feature
- AI Risk / Compliance Secondary feature
- Enterprise App / Internal Tool Builder Secondary feature
Show all 32 attributes
- AI Workflows Secondary feature
- AI Automation / Business Process Automation Not emphasized
- AI Fine-tuning / Custom Model Training Not emphasized
- Agent Builder / Agent Configuration Not emphasized
- Multi-agent Orchestration / Runtime Secondary feature
- System / API Integration Secondary feature
- Prompt Management / Prompt Engineering Not emphasized
- Retrieval-Augmented Generation Secondary feature
- Graph RAG / Knowledge Graph Retrieval Not emphasized
- Enterprise Search / Knowledge Management Not emphasized
- AI / LLM Data Pipeline Not emphasized
- Document AI / Document Processing Not emphasized
- Model Deployment / Inference Infrastructure Not emphasized
- Traditional Machine Learning Not emphasized
- AI Quality Assurance / LLM Evaluation Primary focus
- AI Observability / Monitoring Secondary feature
- AI Security / Guardrails Secondary feature
- Data Privacy / PII / Confidential AI Not emphasized
- AI Governance / Policy Management Secondary feature
- AI Risk / Compliance Secondary feature
- AI Asset Inventory / Model Registry Not emphasized
- Human-in-the-Loop Review / Feedback Not emphasized
- Call Transcription / Speech-to-Text Data Capture Not emphasized
- Conversation Intelligence / Speech Analytics Not emphasized
- Text Chatbots / Conversational Assistants Not emphasized
- Voice AI Agents Not emphasized
- Voice Infrastructure / STT / TTS Not emphasized
- AI for Customer Experience / Support Automation Not emphasized
- Sales / Revenue Intelligence Not emphasized
- Analytics / BI / Decision Intelligence Not emphasized
- Enterprise App / Internal Tool Builder Secondary feature
- Vertical-Specific AI Not emphasized