AIConsole has been serving as enterprise AI for several years, but not everyone has a clear picture of what it actually does. Below you’ll find a straightforward glossary entry that explains what it is, how it works, and why companies use it.

What is AIConsole?

It is an AI Orchestration and Integration platform for enterprise scale solution developed by 10Clouds. It brings together LLMs, data and automation tools into governed workflows and AI agents. It was initially born from open-source origins but has since been offered as a white-label and ready-for-enterprise platform.

How Does AIConsole Work?

The platform is a model-agnostic layer that enables users to change among large language models without vendor lock-in. It's designed as an agent and action oriented framework, where AI agents can take predefined actions like making API calls or executing code in a secure sandbox. The platform links with enterprise knowledge sources such as wikis, Google Drive and CRM systems, enabling subject matter experts to organize information into a knowledge hub for retrieval-augmented generation. It also includes governance capabilities like role-based access control, audit trails, and adherence to regulatory standards including the EU AI Act and ISO 27001.

Key Features

AIConsole is devised in an adaptable architecture which can accomodate various models/tools. It offers a flexible agent and action system for automation, knowledge base with vector search for faster retrieval, and a white label interface which can be adopted as per company branding. Security and regulatory needs are addressed with enterprise-class access controls and logging.

Benefits

The platform allows enterprises to fast-track time-to-market of AI products, typically cutting development times by half. It decreases the operational cost by providing reusable components and helps maintain data privacy by having on-premise deployment options. The platform does this by allowing cross-platform automation, and supporting both open-source and proprietary models, which increases productivity and minimizes the dangers of vendor lock-in.

Use Cases

AIConsole adopted in many sectors. For financial services, they use it to enable AML (anti-money-laundering) by orchestrating end-to-end review pipelines that integrate internal wikis, CRM systems, and external registers and cut the processing times from three weeks down to ten days – a 40% reduction. On the customer experience side, it drives company-branded chatbots and GPT-like assistants; on the internal operations side it automates tasks, reporting and data analysis.

Types of AIConsole

The platform is available in several forms.

Enterprise Platform

Brings the complete orchestration and governance suite to large enterprises.

White-Label AI

Offers premade building blocks and tailor-made interfaces for startups and enterprises that aim to launch AI branded products in no time.

Playground Edition

Ready for on-site installation, allows prototyping and testing.

How to Choose the Right One

Choosing our solution is a matter of evaluating if the platform fits to what your organization needs. Things to watch for include compliance and data control, especially in sensitive or regulated industries; model optionality, as well as the ability to manage cost through multi-model routing; and agent safety with features such as sandboxing and guardrails. You should also consider the degree to which content and knowledge are integrated with existing core sources, whether governance capability and collaboration tools (eg RBAC or shared workspaces) will meet internal requirements, and how much you can get going out of the box before it really delivers value – eg starter kits/ref agents etc. Finally, it is important to keep in mind the total cost of ownership, such as on licensing and scalability which is an indication if this investment will be a long term one.