Yellow.ai
Enterprise conversational AI platform with multi-LLM orchestration
Enterprise conversational AI platform with embedded RAG capabilities processing 16 billion+ conversations annually. Multi-LLM orchestration across 35+ channels and 135+ languages with proprietary YellowG LLM claiming <1% hallucination rates.
Overall Rating
4.3
450 reviews
Features4.4
Ease of Use4.1
Support4.3
Value4.0
Performance4.3
Company Information
Founded
2016
Headquarters
San Mateo, CA, USA / Bengaluru, India
Company Size
501-1000 employees employees
Funding
$102M+ total funding (Series C: $78.15M led by Sapphire Ventures in 2022)
Pros
- Genuinely comprehensive 35+ channel coverage: WhatsApp BSP, Messenger, Instagram, Telegram, Slack, Teams, voice, SMS
- Exceptional compliance credentials: SOC 2, ISO 27001/27018/27701, HIPAA, GDPR, PCI DSS, FedRAMP
- Multi-region data centers (US, EU, Singapore, India, Indonesia, UAE) with customer-selected residency
- 135+ language support with regional variants (Komodo-7B for Indonesia market)
- Proprietary YellowG LLM claims <1% hallucination rate vs GPT-3's 22.7% (vendor benchmarks)
- 0.6-second average response time for conversational AI at scale
- Gartner Magic Quadrant 'Challenger' status validates enterprise credibility (2023/2025)
- Proven scale: 16 billion+ conversations annually, customers include Sony, Domino's, Hyundai, Volkswagen
- On-premise and private cloud deployment options for regulated industries
- Mobile SDKs well-documented with complete code examples (Android, iOS, React Native, Flutter, Cordova)
- G2 ratings: 4.4/5 (106 reviews), 90% recommendation rate on Gartner Peer Insights
- Dynamic AI Agent enables zero-training deployment with auto model routing
Cons
- NOT a RAG-as-a-Service platform - RAG embedded within closed conversational platform, not exposed as API
- No dedicated RAG APIs for direct knowledge base querying or programmatic document upload
- No bot/agent creation or management via API - requires UI-based workflow development
- No embedding or vector store access via API - closed architecture
- No Python SDK - only mobile SDKs (Android, iOS, React Native, Flutter, Cordova)
- Web SDK lacks npm package - requires script tag injection (criticized as 'hit and miss' by reviewers)
- Missing cloud storage integrations: No Google Drive, Dropbox, or Notion support
- No YouTube transcript ingestion natively supported
- Rate limits not publicly documented, no OpenAPI/Swagger specification
- Extremely limited free tier: 100 MTUs, 2 channels - useful only for evaluation
- Enterprise pricing requires sales engagement, ~4-month implementation timeline typical
- Steep learning curve noted in G2 reviews - 'setup felt akin to solving a Rubik's cube blindfolded'
- Documentation gaps cited by developers, especially for web SDK
- GPT-4 and Claude support not explicitly confirmed in documentation
- Analytics data export not available via API - UI-based reporting only
- No analytics API publicly documented for programmatic access
Best Use Cases
Enterprise omnichannel customer experience automation at massive scale (16B+ conversations/year)
Multi-language global deployments (135+ languages with regional variants)
Regulated industries requiring HIPAA, FedRAMP, PCI DSS compliance (healthcare, government, finance)
Voice AI and IVR automation for contact centers and telephony systems
Asia-Pacific market focus with regional data centers (Singapore, India, Indonesia, UAE)
E-commerce and retail customer support (Lulu Hypermarket: 3M+ users in 4 weeks)
Enterprise brands requiring white-label conversational AI (Sony, Domino's, Hyundai, Volkswagen)
Organizations needing on-premise or private cloud deployment for data sovereignty
Multi-channel engagement requiring WhatsApp BSP provider status
Large enterprises with budget for ~$10K-$25K+ annual spend and 4-month implementation
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