Together
The fastest cloud platform for building, deploying, and scaling generative AI applications
About Together
Challenges It Solves
- Building and deploying generative AI models requires specialized infrastructure and expertise
- High computational costs and inefficient resource utilization slow down AI innovation cycles
- Limited access to optimized model architectures and inference optimization techniques
- Scaling AI applications across teams and regions introduces complexity and latency
- Lack of unified platform for model development, testing, and production deployment
Proven Results
Key Features
Core capabilities at a glance
High-Performance Inference Engine
Lightning-fast model inference optimized for scale
Sub-100ms latency for enterprise workloads
Multi-Model Support
Deploy open-source and proprietary models seamlessly
Support for Llama, Mixtral, Falcon, and 100+ models
Fine-Tuning & Training
Customize models for specific business needs
40% faster fine-tuning with optimized pipelines
Distributed Computing
Automatic scaling across multiple GPUs and regions
Horizontal scaling for unlimited concurrent requests
API-First Architecture
Simple REST and gRPC APIs for easy integration
Deploy production models in minutes, not weeks
Cost Optimization
Pay-per-token pricing with no hidden infrastructure fees
50% lower costs compared to traditional cloud providers
Ready to implement Together for your organization?
Real-World Use Cases
See how organizations drive results
Integrations
Seamlessly connect with your tech ecosystem
Hugging Face
Direct integration with Hugging Face Model Hub for seamless model discovery and deployment
Python/LangChain
Native support for LangChain framework for building AI applications with minimal code
REST APIs
Standard HTTP APIs enable integration with any application stack or programming language
OpenAI-Compatible API
Drop-in replacement for OpenAI API endpoint for simplified migration and compatibility
Docker & Kubernetes
Containerized deployment support for on-premise and hybrid cloud architectures
MLOps Platforms
Integration with monitoring and observability tools for production AI workflows
AWS/Google Cloud
Native cloud provider integrations for multi-cloud AI deployment strategies
Implementation with AiDOOS
Outcome-based delivery with expert support
Outcome-Based
Pay for results, not hours
Milestone-Driven
Clear deliverables at each phase
Expert Network
Access to certified specialists
Implementation Timeline
See how it works for your team
Alternatives & Comparisons
Find the right fit for your needs
| Capability | Together | Giselle | AI2image | Macky |
|---|---|---|---|---|
| Customization | ||||
| Ease of Use | ||||
| Enterprise Features | ||||
| Pricing | ||||
| Integration Ecosystem | ||||
| Mobile Experience | ||||
| AI & Analytics | ||||
| Quick Setup |
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