Marktechpost releases 2025 Agent AI and AI Agent Report: The technical landscape of AI Agent and Agent AI

Marktechpost AI Media has released its most comprehensive publication –Agent AI and AI Agent Report 2025– Technically rigorous exploration of the architecture, framework and deployment strategies that shape the future of AI agents. The report covers a complete proxy AI stack, mapping an ecosystem designed based on inference-capable models, memory frameworks, and orchestration engines designed specifically for the real world.

Redefine AI with autonomous

Unlike traditional assistants, proxy AI systems are defined by their ability to operate independently, make decisions and learn over time. These agents are not only language model wrappers, but also integrate planning, tool usage, multimodal understanding, and continuous memory. The transition from timely interaction to autonomous goal execution marks the fundamental evolution in AI utilities.

Agents clarify actions: perform tasks, integrate context across modes, work with humans or other agents, and iteratively refine their strategies. This proactive behavior distinguishes them from a robot or assistant that relies on pre-programmed logic or reactive instructions.

Agent Architecture: Modular Stack

The report breaks down the anatomy of modern AI agents into different modular components:

• Model (core reasoner): LLM and multimodal transformers are generated, explained and rationally on advanced goals.
• Tool interface: The APIs, browsers, and databases used by the agents interact with the digital environment.
• Memory system: The mechanism of plot and semantic memory achieves long-term coherence and personalized behavior.
• Role and Intent Layers: Role-based behavioral modeling that guides tone, task range, and interaction design.
• Orchestra layer: Manage state, workflow execution, retrieval and inter-agent communication across distributed environments.

The architecture supports single-grid pipelines and collaborative multi-agent systems, designed to coordinate task execution in complex enterprise workflows.

Agent Development Framework

Marktechpost’s report is classified into 25 production-level platforms and frameworks. Among them, it is worth noting:

• CREWAI: High-performance multi-agent framework that provides low-level control, is ideal for enterprise-level orchestration.
• Langgraph: A graph-based framework that enables state flow agent workflow with built-in observability and moderate hooks.
• Google Vertex AI Agent Builder: Agent2Agent (A2A) protocol that provides cross-frame proxy interoperability provides managed runtime.
• Salesforce Agentforce: Built on the data cloud, it supports action orchestration of CRM systems with trust and design compliance.

These platforms demonstrate various approaches (from codeless prototypes to code-first orchestration), while aligning around common principles: memory retention, tool interoperability, and synthesisable logic.

Infrastructure, evaluation and observability

This report describes a broader operating stack basic proxy system:

• Model Services and Hosting: Similar platforms Fireworks AI,,,,, Betneyand OpenRouter Provides optimized inference APIs and infrastructure for large and small models.
• Memory engine: Solution Zep,,,,, Whyhow.aiand contextual.ai Introduce structured memory mechanisms optimized for dynamic information retrieval and adaptive planning.
• Assessment and Safety: such as tools Patron AI,,,,, Hayz Laboratoryand Inspeq AI Provides evaluation frameworks, traceability, hallucination detection and failure prediction – trust and compliance.
• Observability layer: Similar framework Agent Provide real-time tracking, cost analysis and debugging capabilities in LLM and multi-agent deployments.

It is particularly noteworthy that Discomfortable AIan open source toolkit for low-cost fine-tuning and quantification of open models such as fuchsia and QWEN. It enables developers to train domain-specific agents using comprehensive data, i.e. offline and consumer-grade hardware.

The future of integration

Agent AI is shifting from theoretical commitment to operational reality. Marktechpost’s 2025 report highlights the industry’s accelerated drive to blend language, reasoning and software interactions into cohesive autonomous systems.

As organizations embed cross-domain agents (from customer service to supply chain orchestration), the focus will shift to long-term memory, scalable orchestration and powerful evaluation metrics that go beyond traditional benchmarks. The future of AI will not be scripted by scripts – it will be a proxy.

Access the full report: Download from Marktechpost