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Enterprise AI platform where marketing, sales, and support teams build governed AI agents on Writer's own Palmyra models.
Chinese AGI company building multimodal LLMs, Hailuo video, speech and music models, plus AI apps and open APIs.
Weights & Biases is a widely used MLOps platform for experiment tracking, model management and evaluating AI applications.
Enterprise Work AI platform for company-wide search, an AI assistant and building governed agents across 250+ connectors.
Open-source AI gateway giving dev teams unified access, fallbacks and spend tracking across 100+ LLMs.
No public pricing
Free trial available
No public pricing
No public pricing
Free trial available
- ✦WRITER Agent for delegating end-to-end tasks in natural language
- ✦Agent Playbooks for repeatable, on-brand workflows
- ✦AI Studio for building custom agents on company data
- ✦Knowledge Graph for grounding agents in company-specific context
- ✦Palmyra proprietary LLMs built for regulated enterprises
- ✦Enterprise security, identity, and compliance controls for IT
- ✦MiniMax M-series LLMs (M3, 1M context, MSA)
- ✦Hailuo AI video generation
- ✦Speech and music generation models
- ✦MiniMax Code agentic coding tool
- ✦Consumer apps (Hailuo, Xingye)
- ✦Open API and Token Plan for developers
- ✦Experiment tracking and visualization for ML training runs
- ✦Model and artifact versioning and management
- ✦Hyperparameter optimization tooling
- ✦Collaborative dashboards and reports for ML teams
- ✦LLM application tracing and evaluation tooling
- ✦Enterprise search across company apps
- ✦Personal AI assistant grounded in work data
- ✦Agent builder, orchestration and governance
- ✦250+ connectors and actions
- ✦Enterprise knowledge graph and hybrid search
- ✦Security controls for scaling AI
- ✦Unified access to 100+ LLMs in OpenAI format
- ✦Cost/spend tracking per key, user and team
- ✦Budgets and rate limiting
- ✦Automatic provider fallbacks and retries
- ✦Virtual keys and team management
- ✦Logging and observability integrations
- →Automating on-brand marketing content production at scale
- →Handling inbound customer support responses with AI agents
- →Building custom AI agents connected to a company's internal systems
- →Enforcing brand voice and terminology consistency across teams
- →Deploying AI under enterprise security and compliance requirements
- →Coding and agentic tasks
- →AI video generation
- →Text-to-speech and music creation
- →Building on MiniMax model APIs
- →ML engineers tracking and comparing training experiments
- →Research teams versioning datasets and model checkpoints
- →Teams building and evaluating LLM-powered applications
- →Organizations collaborating on machine learning projects
- →Search across all company knowledge
- →Answer employee questions with grounded AI
- →Build and deploy custom AI agents
- →Automate cross-system workflows
- →Giving developers governed access to many LLMs
- →Attributing and controlling LLM spend
- →Keeping apps running during provider outages