Arya.ai Launches APEX MCP to Make LLMs Domain-Specific
Arya.ai has unveiled its latest innovation: APEX MCP (Model Context Protocol), a client-server orchestration layer that transforms general-purpose large language models (LLMs) into reliable domain-specific AI tools. This launch aims to eliminate the common pitfalls associated with using LLMs in high-stakes industries—hallucinations, inconsistency, and low reliability.
Wrapping Domain Knowledge Around Any LLM
At the core of APEX MCP is a modular layer of pre-trained applications. These modules wrap domain context around an LLM, ensuring that outputs are not just accurate, but also traceable and verifiable. Unlike traditional prompting methods that attempt to steer LLM behavior, this protocol introduces a structured approach where each step is governed, validated, and auditable.
Instead of relying on fragile prompts, APEX MCP adds rigor by integrating verified domain logic before and after each AI interaction. It’s a leap forward in aligning LLMs with real-world business demands.
Also read: StorONE and Phison Deepen Partnership to Launch AI-Native On-Premises Storage for LLM Training
Over 100 AI Modules for Cross-Industry Needs
Arya’s APEX platform now comes equipped with more than 100 pre-built AI modules. These modules support tasks across finance, compliance, insurance, customer experience, and privacy. Teams can create workflows that, for example, assess credit risk, detect document fraud, analyze audio, or process insurance claims—all while staying within a secure and governed framework.
Users can browse the modules via a searchable catalog, connect them through APEX’s no-code interface, and invoke them using JSON-RPC. Modules can be chained together to create seamless flows such as PII Redaction → Sentiment Analysis → Executive Summary, making AI automation more practical and production-ready.
LLM-Agnostic, Audit-Ready, and Plug-and-Play
The MCP Server handles discovery, execution, and logging of modules. Meanwhile, the MCP Client takes care of integrating LLMs with pre- and post-processing steps. Since the protocol is LLM-agnostic, enterprises can plug in any foundation model of their choice—no retraining or app rewrites needed.
What makes the platform stand out? For one, it’s audit-ready—every prompt, response, and output is logged. It also supports zero-rewrite integration, which means teams can add or swap modules without modifying core application logic. This saves time, reduces risk, and accelerates deployment.
Real-World Applications Across Industries
With APEX MCP, banks can parse transactions, assess financial risk, and compile regulatory reports—without bouncing between tools. RegTech companies can automate compliance flows with embedded audit trails. And customer service teams can extract insights from support tickets, categorize issues, and suggest next steps—all within a single orchestrated workflow.
This modular architecture removes the need for custom coding or complicated integrations. Instead, businesses gain the ability to rapidly scale verified AI processes with confidence.
Early Access and What’s Next
Arya.ai, now part of Aurionpro, is opening early access to its APEX + MCP Sandbox. This environment will allow enterprises to explore chaining modules, configuring LLMs, and orchestrating end-to-end workflows using real data and a visual UI.
Whether used for automation, compliance, customer support, or risk management, APEX MCP gives teams full control over how AI is deployed—making every interaction traceable and reliable by design.
With this launch, Arya.ai is positioning itself at the forefront of domain-verified, compliant AI workflows, built one module at a time.
