AI Engine
Synergy of agent-based services and AI Engine ecosystem

Synergy of agent-based services and AI Engine ecosystem

The AI Engine allows users and developers to connect to a wide range of agent-based services. Once an agent is registered ↗️ the service is visible to the AI engine and it can start connecting users and services together.

This next-generation system boasts personalized capabilities, powered by an internal agent, to harmonize tasks seamlessly. Indeed, the AI Engine internally spawns a personal agent for use and once you have given it your intent, it can asynchronously start working on your behalf.

At its core lies the immense power of LLMs (Large Language Models), driving the engine's understanding, coordination, planning and problem-solving proficiency.

Catalyzing connections

The AI Engine ushers users and developers into a unified ecosystem of agent-based services. Once registered within the system, this innovative service becomes an integral part of the AI Engine's landscape, orchestrating dynamic connections between users and services.

Unveiling the intent's architecture

At the heart of the AI Engine's operation lies a sophisticated architecture comprising two pivotal components: Objectives and Tasks.

  • Objectives: these are the bedrock of the AI Engine's endeavors, encapsulating users' overarching goals in natural language, fueling the engine's purpose and direction.

  • Tasks: a dynamic sequence of steps that fuels the achievement of defined objectives. In their complexity, tasks often involve resource allocation, temporal considerations, and interdependencies, efficiently executed by agent-based services.

Deconstructing tasks

The AI Engine's essence is distilled into two profound functions:

  1. Comprehension and planning: this core process takes your objective and transforms it into a meticulously curated series of sub-tasks, each representing an integral step towards the desired outcome. This orchestration can be unfolded autonomously or, in some cases, with the user's input to validate tasks selection.

  2. Building context: the AI Engine is a skillful collector and transformer of information, perpetually enriching its understanding. Contextual enhancement is a continuous endeavor, refining the knowledge landscape happening continuously throughout the session with the AI Engine. In other words, Context building is the continuous process in which additional information is collected and/or transformed in order to complete a task.