How Codesphere AI Suite streamlines AI development
AI Suite
The AI Suite was built from the ground up for production-grade AI projects. We treat AI as software, applying the same robust principles of development and operations that you expect from traditional software engineering.
Unified Development Model
Experience consistent processes and a unified deployment technology for both traditional applications and AI solutions.
Hosting & Resource Utilization
Efficient hosting and patented resource management for both inference and training, whether in the cloud or on-prem.
Self-Service for Teams
Empower developers and data scientists with self-service capabilities, without the need for deep cloud or MLOps expertise.
No Vendor Lock-in
Operate your own models and workloads with complete control over your data and execution environment.
Codesphere's self-service model lets developers take control of their entire deployment process
The three layers of our AI Operating System
Full flexibility: Modules can be adjusted according to custom workloard including models, data sources, frameworks
Human-like automation
Agents
Ready-to-use AI applications for specific business needs such as document analysis and comparison, knowledge databases, or support bots, fully customizable.
Building blocks and low code
Bricks
Reusable services and tools to accelerate AI development, including components for RAG, vector search, code generation, analysis, and testing.
Infrastructure, Models, and Custom Code
Bedrock
Scalable and cost-efficient infrastructure for all AI inference and training workloads:
- Scalable, cost-efficient CPU/GPU resources for AI models
- Automatic load balancing and fast deployment
- Simplified infrastructure management (network, security, scaling)
Agents tailored to your use case
Custom AI Agents
We build customized AI agents that integrate securely into your existing infrastructure and data environment. These agents continuously enhance and expand your AI suite with new capabilities.
We have collaborated with our clients on agents that can then be implemented into the standard creates a win-win situation.
Document comparison agent for L-Bank