CHAPTER 1
The next horizon of AI Agents is reliably transactional Agentic Commerce, which requires new paradigms of agentic networks, transaction protocols, state and context handling, and user interaction and delegation. We are focusing on smart transactional AI agents that can configure, sell, book, and pay for products and services through a peer-to-peer agentic transaction protocol.
The promise of tectonic market shifts through AI, and specifically AI Agent technology, "feels like 1996" to many. Its huge promise is compounded by immature technology and hype. The parallels don't end there: While LLMs entice users through Turing-capable interaction, and browser-based agents and automation simulate agentic action, truly agentic transactions are not yet possible.
Current "agentic" solutions are either hard coded workflows or flat orchestrating layers that remote-control a browser instance. Although a logical step in the right direction, the monetization of true agentic verticals will not be based on remote-controlled browser instances running in a virtual machine.
To enable a new era of agents that act independently, make self-directed decisions, and perform complex transactions without continuous human oversight, a new agentic web is required.
Agentic AI is poised to displace traditional SaaS models by transforming static applications into dynamic, purpose-driven autonomous systems. Likewise, E-commerce marketplaces will be replaced by Agentic Commerce networks running on protocols that first supplement, then replace Web2 architectures.
We are pioneering Transactional AI Agents, a new category of Agentic AI that enables direct peer-to-peer, cryptographically validated transactions, hyperdelegation, and conditional transfers, setting a new standard beyond personal and workflow agents.
AI Agent technology holds immense promise but is currently hindered by immature technology and overhyped expectations. Truly independent "agentic" transactions remain out of reach with today's solutions.
Current agentic solutions rely on hardcoded workflows or browser remote-control. A new agentic web infrastructure is essential to support autonomous agents capable of self-directed decisions and complex transactions without constant human intervention.
Agentic AI is set to disrupt traditional SaaS models by "agentifying" static applications into dynamic, autonomous systems. Similarly, e-commerce marketplaces will evolve into Agentic Commerce networks, built on protocols that will replace Web2 architectures.
CHAPTER 2
Truly autonomous agents should fully understand the intentions of their users and reliably execute them across a wide range of suppliers. This requires an agentic framework that is intent-aware, decentralized, and capable of autonomous agent to agent negotiation. With the adoption of Model Context Protocol (MCP), IBM’s ACE, and Google’s A2A Standards, the AI industry is moving towards accepted protocols for agentic interaction. Agentic Systems is focused on developing an interoperable platform for secure, reliable Agentic transactions that allows companies to implement these and other protocols in industry specific architectures. Thus companies can adapt to the paradigm shift of consumers and business away from the Search and Click paradigm of the Web to Voice first, intent-driven user journeys enabled by Personal Agents.
The Agentic Systems Platform bridges the gap between personal agent interaction and supply side agentic transaction enablement. To achieve this, the architecture of our platform defines the following key components:
To achieve this, we have developed the following key components:
Individualized agents that understand user intent and preferences, and can autonomously delegate these intents to other agents.
Discrete specialized seller agents that can interpret delegated user intent and correctly infer the necessary orchestration of sub-agents and function calls.
Agent nodes that can retrieve, parse, and transact on supplier inventories following industry or company specific ontologies and business rules.
A connected ecosystem of specialized agents that collaborate across domains, providing seamless integration of services while maintaining individual autonomy and specialization domains and employing an array of specialized node agents, such as:
Agents that maintain and traverse interconnected data structures to provide contextual insights and identify relevant relationships between entities.
Specialized agents focused on validation of information, transactions, and outcomes to ensure trustworthiness and compliance with business rules and standards.
Meta-agents that coordinate complex workflows across multiple specialized agents, optimizing process efficiency and ensuring coherent execution of multi-step operations.
Adaptive agents that improve performance through continuous feedback, updating their models and approaches based on outcomes and evolving user preferences.
AI Agent technology holds immense promise but is currently hindered by immature technology and overhyped expectations. Truly independent "agentic" transactions remain out of reach with today's solutions.
Current agentic solutions rely on hardcoded workflows or browser remote-control. A new agentic web infrastructure is essential to support autonomous agents capable of self-directed decisions and complex transactions without constant human intervention.
Agentic AI is set to disrupt traditional SaaS models by "agentifying" static applications into dynamic, autonomous systems. Similarly, e-commerce marketplaces will evolve into Agentic Commerce networks, built on protocols that will replace Web2 architectures.
CHAPTER 3
Agentic Systems is differentiated by voice-enabled UX, decentralized architecture, and AI agents that are context-aware, goal-oriented, interoperable, and transactional, leveraging peer-to-peer agentic protocols.
The Agentic Systems Platform bridges the gap between personal agent interaction and supply side agentic transaction enablement.
To achieve this, we have developed the following key components:
Our embedded agents translate legacy system inputs and outputs into our agentic framework and protocol, enabling precise function calls and the completion of validated transactions.
Agentify allows suppliers of transactional inventory to self-onboard embedded agents and establish transaction pipelines to backend legacy systems.
Our Embedded Agents are geared towards function calls both through our validated agentic network, as well as through non-validated function calls from market leading Personal Agents such as ChatGPT, Claude, Manus, and others. From a supplier perspective, the Embedded Agents thus provide GenAI EO value in addition to the integration into our validated Agentic P2P network.
Likewise, our Embedded Agents serve dedicated Context Protocol servers, both in non-validated iterations and in dedicated vertical iterations co-developed with market-leading inventory providers.
Task and agentic function call orchestration within our platform is handled in a dedicated layer that enables autonomous Agents to interact, advise, sell, book, and pay.
To achieve precise integration of supplier and product content into user interaction of GenAI Personal Agents, our multi-agent orchestration includes function calls to dedicated agents that retrieve real-time inventory data from legacy sources and embedded agents alike.
The harmonization of inventory data across myriad embedded agents is ensured by applying vertical market ontologies developed and established with market leading suppliers. These onotologies also inform the Context Protocols we apply.
Transaction security, Privacy, and AI sovereignty are ensured by the decentralized validation of delegated user intent and preferences. This is achieved through web3 paradigms and the differentiation of Provider, Issuer, Holder, and Verifier credentials for each transaction.
Our Agentic P2P Network includes a distinct agentic protocol, enabling direct Agent to Agent transactions without relying on Web2 interaction. This is a paradign shift from browser executed Personal Agent operator models.
Applying Turing-capable, sentiment adjusted real-time voice interaction, we implement LLM-agnostic WebRTC Frameworks to ensure authentic and competent, hallucination-free interaction with the user.
The context window of real-time, voice first NLP interaction with the user is enhanced by AppAware, a technology that blends generative chat interaction with multimodal interfaces in any distribution scenario on any screen with precise function calls through our multi-agent orchestration.
Beyond Agentify, we expect to launch a self-onboarding platform for consumer-facing agents with flexible context settings to address a variety of vertical market implementations.
AI Agent technology holds immense promise but is currently hindered by immature technology and overhyped expectations. Truly independent "agentic" transactions remain out of reach with today's solutions.
Current agentic solutions rely on hardcoded workflows or browser remote-control. A new agentic web infrastructure is essential to support autonomous agents capable of self-directed decisions and complex transactions without constant human intervention.
Agentic AI is set to disrupt traditional SaaS models by "agentifying" static applications into dynamic, autonomous systems. Similarly, e-commerce marketplaces will evolve into Agentic Commerce networks, built on protocols that will replace Web2 architectures.