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Infrastructure company building large-scale GPU data centers and compute for AI, including Anthropic's compute buildout.
Enterprise voice-AI platform for building phone agents on dedicated infrastructure, with per-minute pricing and HIPAA/SOC2/PCI compliance.
Platform for building and interacting with AI-powered virtual beings.
Developer API suite (Reader, Embeddings, Reranker) that turns web content into LLM-ready data for search and RAG.
Pay-as-you-go API aggregating thousands of image, video, audio and LLM models with custom inference hardware for lower per-request cost.
No public pricing
Free trial available
No public pricing
No public pricing
Free trial available
- ✦Large-scale GPU and data-center infrastructure for AI
- ✦Power acquisition and data-center design/build
- ✦Fast deployment (gigawatts in ~6 months)
- ✦Operates both hardware and software stack
- ✦AI phone agents (inbound and outbound)
- ✦No-code agent builder (Norm)
- ✦Scenario testing before launch
- ✦Omnichannel voice, SMS, iMessage and chat
- ✦Telephony and CRM integrations
- ✦Enterprise compliance and on-prem options
- ✦AI chatbot creation with unique personalities and voices
- ✦Decentralized platform for AI-native apps
- ✦Voice and video conversations with AI beings
- ✦AI agent building and sharing
- ✦Creator economy for AI apps
- ✦Reader API converts URLs to Markdown
- ✦Multimodal multilingual embedding models
- ✦Reranker for stronger search relevance
- ✦Web search endpoint returning SERP data
- ✦MCP server for use inside LLMs
- ✦Native inference inside Elasticsearch
- ✦Single API for image, video, audio, 3D and LLM models
- ✦Standardized model addressing across hosted, partner and custom uploads
- ✦Support for LoRAs, ControlNets, VAEs and embeddings on open-source models
- ✦WebSocket and REST access with async webhook delivery
- ✦Pay-per-request billing with no infrastructure to manage
- ✦Raw serverless GPU/CPU compute for custom workloads
- →Training and running large AI models at scale
- →Provisioning GPU compute for AI labs
- →Building dedicated AI data-center capacity
- →Automating customer-service calls
- →IVR replacement and appointment booking
- →Outbound sales and lead qualification
- →Regulated-industry voice automation
- →Interacting with AI friends like Shizuku for voice and video conversations
- →Creating AI-native apps using generative AI models
- →Building and sharing AI agents within the MyShell ecosystem
- →Ground LLMs with clean web content
- →Build semantic and RAG search
- →Rerank retrieved results
- →Give AI agents live web access
- →Adding AI image or video generation to an app without managing infra
- →Batching multi-modal generation tasks in one API call
- →Running custom fine-tuned models via Model Upload
- →Cutting inference costs at high generation volume