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Technologies

MCP-powered platform uniting AI Agents into a single ecosystem

Published February 10, 2026
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By shifting from isolated AI pilots to a centralized enterprise framework, businesses can finally automate complex workflows and accelerate decision-making without compromising on governance or LLM independence. Here’s how we solve these scaling challenges with our enterprise-ready solution.

MCP-powered AI Assistant by WaveAccess

Is your AI strategy stuck in pilot purgatory?

While many organizations have experimented with AI, most find themselves stuck with a fragmented patchwork of disconnected tools that create data silos and security risks. We’ve identified that the critical barrier to scaling is the lack of a unified, vendor-agnostic architecture capable of bridging corporate knowledge with secure, multi-agent automation.

Solution

WaveAccess’s AI Assistant is an MCP-powered platform that unites multiple tech-agnostic AI agents within one ecosystem and enables their connection to external tools, data sources or services. It makes AI more accurate and useful in various business tasks.

AI Assistant combines multi-agent architecture, cloud & on-prem deployment options, and enterprise-grade scalability.

Strategic value

  • Centralize knowledge and workflows in one secure platform
  • Accelerate analytics and decision-making
  • Reduce manual workload through intelligent automation
  • Stay independent from a specific LLM vendor

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Key features

  • Multi-agent architecture: Platform orchestrator coordinates AI agents to operate as one system
  • Flexible UI: AI portal, AI chat within a dashboard, or embedding into existing corporate environments
  • Any agents integration: A universal adapter of any tech-agnostic agents, that comes with ready-to used backend and therefore fast deployment
  • Scalable design: From pilot projects to enterprise-wide deployments
  • On-Prem or Cloud: Deploy securely within your infrastructure
  • Enterprise governance: Transparent data flow, full access control, and compliance

Use cases

  • Conversational BI: Ask questions in natural language to get analytical insights, generate repor ts or create dashboards in different formats
  • Knowledge Management: Aggregate and retrieve information from diverse sources — documents, emails, databases, and internal systems
  • Process Automation: Combine agents to handle repetitive or multi-step workflows
  • Decision Support: Deliver concise, context-aware insights for informed business actions

How it works

AI Assistant leverages the MCP framework to power a flexible multi-agent architecture, combining advanced workflow orchestration with diverse functionality and seamless scalability

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