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Applied-AI studio and R&D group building enterprise products like the FeatureOS feedback platform for product teams.
Unified API gateway that routes requests to 400+ LLMs across 70+ providers with failover and no subscription.
Serverless AI cloud for running inference, training and sandboxes on GPUs with fast cold starts and pay-per-use billing.
Enterprise Work AI platform for company-wide search, an AI assistant and building governed agents across 250+ connectors.
General-purpose autonomous AI agent that plans and runs multi-step tasks such as building sites, slides and research in the cloud.
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- ✦In-house product line including FeatureOS and SupportWire
- ✦Feedback board, roadmap, changelog, and knowledge base modules (FeatureOS)
- ✦AI-powered feedback analysis and duplicate detection (FeatureOS)
- ✦API and webhook access for custom integrations
- ✦Applied AI R&D consulting engagements
- ✦Product engineering services for client teams
- ✦One unified, OpenAI-compatible API for 400+ models
- ✦Automatic provider failover for higher uptime
- ✦Edge routing for low latency
- ✦Custom data and provider policies
- ✦Pay-as-you-go credits usable across any model
- ✦Serverless GPU compute defined in Python
- ✦Sub-second container cold starts
- ✦Autoscale 0 to 1000+ GPUs
- ✦Inference, training and batch workloads
- ✦Secure sandboxes for untrusted code
- ✦Built-in logging and observability
- ✦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
- ✦Autonomous multi-step task execution
- ✦Website and app building
- ✦AI slides, design and image generation
- ✦Manus browser operator
- ✦Wide Research mode
- ✦Cross-platform web, desktop and mobile apps
- →Product teams collecting and prioritizing customer feedback (via FeatureOS)
- →Companies needing custom applied-AI research or engineering
- →Startups outsourcing product engineering to a specialist studio
- →Accessing many LLMs through one integration
- →Adding provider redundancy to AI apps
- →Comparing model price and performance
- →Powering agents and AI-native products
- →Deploying and scaling model inference
- →Fine-tuning and training models
- →Running batch/parallel AI jobs
- →Executing untrusted code in sandboxes
- →Search across all company knowledge
- →Answer employee questions with grounded AI
- →Build and deploy custom AI agents
- →Automate cross-system workflows
- →Automate end-to-end digital tasks
- →Produce websites and presentations
- →Conduct broad research
- →Hand off browser tasks to an agent