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Developer API that gives AI agents persistent memory, retrieval, and connectors, usable both as infrastructure and a personal app.
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.
Serverless platform for running and fine-tuning image, video, audio and 3D generative models via one fast API.
High-performance open-source vector database for production AI retrieval and RAG, for teams needing scale, hybrid search, or self-hosting.
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- ✦Persistent, structured memory built as a knowledge graph
- ✦Sub-300ms hybrid retrieval (RAG) with reranking
- ✦Native filesystem mount for agent memory access
- ✦Connectors to Slack, Notion, Drive, Gmail, GitHub, S3
- ✦Automatic extraction from PDFs, images, and audio
- ✦User profile and behavior tracking across sessions
- ✦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
- ✦1,000+ generative model APIs
- ✦Serverless GPU inference engine
- ✦On-demand and dedicated GPU clusters
- ✦Model fine-tuning and custom deployments
- ✦Bring-your-own-weights and private endpoints
- ✦SOC 2 compliance and enterprise features
- ✦Hybrid dense and sparse vector search (BM25, SPLADE, miniCOIL)
- ✦Advanced metadata filtering applied during search traversal
- ✦Multivector support for multimodal retrieval
- ✦Reranking with score boosting and late-interaction models (ColBERT, MMR)
- ✦Flexible deployment: cloud, hybrid, private, or edge
- ✦Rust-based engine optimized for low-latency, high-scale search
- →Developers adding long-term memory to AI agents
- →Teams building agents that need to sync with existing tools
- →Individuals wanting one memory layer shared across multiple AI assistants
- →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
- →Adding image/video generation to an app
- →Running fast diffusion-model inference at scale
- →Training or fine-tuning custom generative models
- →Building retrieval-augmented generation (RAG) pipelines
- →Powering AI recommendation and semantic search systems
- →Enterprises needing on-prem or hybrid deployment for compliance
- →AI agent platforms needing fast contextual retrieval at scale