Next-generation AI platform with AI Mesh architecture. Multi-model hosting, data management, API compatibility, and full observability for enterprise AI.
Request a DemoModern industry's need for scalable, secure, and flexible AI solutions requires a new model architecture: AI Mesh.
Traditional architectures run AI as isolated services. A mesh approach lets agents collaborate, share context, and handle complex workflows that span multiple systems.
AI Mesh enables multiple specialised AI agents collaborate through shared memory, orchestration protocols and controlled tool access to solve complex tasks more reliably, transparently and at scale.
Inspired by principles from multi-agent systems and modern orchestration standards such as Model Context Protocol (MCP), an AI Mesh enables autonomous reasoning, secure agent–agent coordination and robust execution across heterogeneous environments.
AEL Studio™ adopts a modular, containerized architecture centred on LLM orchestration, data persistence, and API exposure. It integrates embedded LLMs with Kernel Memory for semantic search and retrieval, enabling agentic workflows where agents reason, plan, and invoke tools dynamically.
Ontology runtime + AI agents + audit pipeline + role-based ACL on a shared truth. One semantic layer between your existing systems and the people, agents and dashboards that consume them.
AEL Studio™ is a complete platform for building, orchestrating, and deploying AI solutions on-premise or in a private cloud. The platform includes agent builders, integration engines, orchestration, data warehouses, vector-based memory, real-time execution, and full DevOps support.
Embed and manage models with customizable parameters for context size, tokenization, and function calling.
Kernel Memory for ingesting, indexing, and retrieving data, supporting RAG workflows.
OpenAI-standard endpoints for seamless integration with existing tools and agents.
Connect to ERP, e-commerce, support systems, and other tools through APIs and standard connectors.
Multi-agent and multi-step reasoning (MCP) - enables advanced workflows and fast response times.
Systems monitored with embedded tools or through Open Telemetry for integration to other operational monitoring systems.
AEL Studio™ bundles a complete production-grade AI stack into a single deployment. You don’t need to assemble it from multiple vendors, every component below is included, integrated and operated as one platform.
| Component | Purpose |
|---|---|
| LibreChat | Chat orchestration and user-facing AI interface |
| Flowise | Visual agent builder, low-code agent design |
| n8n | Workflow automation, included natively, connect to ERP, CRM, ticketing, email |
| MCP (Model Context Protocol) | Agent-to-agent coordination, tool calling |
| Kernel Memory | RAG, semantic search, document ingestion and retrieval |
| Qdrant | Vector database for embeddings |
| PostgreSQL | Structured data, application state, embeddings |
| ClickHouse | Analytics, audit trail storage, real-time queries |
| Langfuse | LLM observability, every prompt, completion and tool call traced |
| OpenTelemetry | System-level observability, integration to enterprise monitoring |
| Multilingual-e5-large | Embeddings model (1024 dimensions) |
| mxbai-rerank-large | Reranking model for retrieval quality |
All components are open source under Apache 2.0 / MIT licenses, deployed as Kubernetes-native containers. The customer owns the deployment, the data, and the audit trail.
Contact us for a technical deep-dive.