The ES1 ML Framework

The ESML Framework is the ML engine behind the ES1 AI Gateway—giving enterprises an independent, high-performance AI/ML layer that runs where your data lives. Fully containerized and built on PostgresML, it delivers unmatched speed, privacy, and extensibility—without vendor lock-in.

Why Choose ESML Over Hyperscalers?

No more lock-in – Fully containerised and vendor-agnostic
No more compromises – Up to 40x faster inference
No need to move your data – Private, low-latency execution
No proprietary limits – Use 47+ algorithms and open libraries

ESML brings structure to unstructured data, context to language, and memory to intelligent agents—so your AI doesn’t just respond. It reasons.

Key Capabilities

PostgreSQL & PostgresML native
In-database vector search & inference
GPU acceleration
Unified RAG & Graph RAG
47+ ML algorithms
LLMs from Hugging Face
Agentic workflows
Integration with Airflow, Kafka, DBT

Flexibility

Connect data sources and applications to AI without having to move or change your data and avoid impacting existing business processes.

Extensibility

Connect any combination of public, custom, or future LLMs, vector DBs, embedding models, or bots to your enterprise AI ecosystem.

Security

Implement consistent access controls, encryption standards, and monitoring protocols on a per service and per user level.

Scalablility

Maintain your business continuity and governance with AI controls and audit capabilities.

ESML Framework

Deployment Options

on premise deployment

The Enterprise AI Gateway has been developed using standard a standard Kubernetes container architecture. Take advantage of your existing K8s Cluster architecture and administration by deploying directly to your on-premise environment.

By utilising this approach with private LLMs, you can ensure that you have complete control of your enterprise data while still taking advantage of public data sources to supplement the AI queries

deploy in the enterprise cloud of your choice

Nearly 96% of all enterprises use cloud or multi-cloud computing as part of their IT architecture. The cloud computing environment often includes a Kubernetes based environment. Deploy the Enterprise AI Gateway in your cloud computing environment just as you would deploy any other K8s service.

With an enterprise cloud or multi-cloud environment, connectivity is built-in. The Enterprise AI Gateway can take advantage of this and ensure maximum value with no risk to business continuity.