A network designed for simplicity, efficiency, and AI-agency; built from the ground up to be managed by an artificial intelligence, rather than merely monitored by one.
AI agents (LLMs) will be able to:
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Query the network statistics, observe the network state, and make actions on events (like failures, limits, etc)
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Query network packet payloads for AI analysis
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Make general routing changes to the network (FIB)
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Make general security changes (ACL)
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Direct protocol conversion from UDP to MC or MC to UDP.
swXtch.io's new AI native networking platform not only optimized traffic flow but also began predicting failures before they occurred."
An AI-Native Network for the Modern Era
Our solution combines three groundbreaking technologies into one cohesive platform
cloudSwXtch
(Cloud-Native Multicast)
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Broadcast-grade IP multicast in any cloud
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Efficiently delivers video to multiple AI engines and production workflow —at once
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Supports ST 2110 and VC-6 with ultra-low latency
Intelligent Assistant
(Model Context Protocol)
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Direct integration with the MCP AI standard
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Lets AI models dynamically manage their data pipelines
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Secure, programmable, and ready for autonomous operations
Security by Design
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Our architecture runs entirely within your virtual network.
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With built-in MCP governance, swXtch.io acts as firewall, auditor, and guardian for your AI infrastructure.
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Deployed in your tenant, any cloud, or on-prem with role-based controls and auditability.
Use Natural Language for AI-Driven Activity
The AI Native Network turns complex infrastructure into a conversational experience, empowering teams to scale, visualize, and control networks with simple natural language.
Instant Observability
Task
Visualize topology, connections and performance metrics in real time.
Example Prompt
“Show me a graph of my network”
Live Telemetry
Task
Query performance and health stats in plain language across links & nodes.
Example Prompt
"How many flows? Any errors? What are the bit rates, losses, & latency?"
Remediate Issues
Task
Create automated, conditional workflows without scripting or code.
Example Prompt
“If packet loss >2%, trace the affected path and restart the impacted service.”
Operate Anywhere
Task
AI-native orchestration that works across ANY environment.
Example Prompt
“Deploy in my AWS tenant” or “Run locally on-prem.”
Integrate With Existing Tools
Task
Structured event streams for seamless interoperability.
Example Prompt
“Output to my monitoring dashboard in JSON.”
Empower Anyone to Manage Advanced Networks
AI Native Networking from swXtch.io lets non-network engineers operate complex, multicast-enabled environments using natural language commands - no deep expertise required.
Lower Skills Barrier
Manage complex networking environments using natural language commands, without deep technical expertise.
Reduced Headcount
Automate routine management and monitoring, minimizing the need for large network operations teams.
Works Anywhere
Built on open-standards, deploy across on-prem, hybrid, or cloud with full support for multicast and ST 2110 workflows.
Manage Complex Networks with Simple Natural Language Commands
Use-Cases
The AI Native Network turns complex infrastructure into a conversational experience, empowering teams to scale, visualize, and control networks with simple natural language.
Run More Live Events with the Same Team
Scale your operations without scaling headcount.
AI-driven automation and natural language control let your existing team manage more concurrent streams, channels, and network tasks - boosting efficiency without adding complexity.
Enable non-network engineers to manage sophisticated networks
Empower anyone to operate advanced network environments through natural language commands.
No deep networking expertise required - just ask, and the AI Native Network translates intent into precise actions.
Visualize topology and remediate issues faster
See your entire network at a glance and fix problems in real time.
Ask for insights, trace errors, or trigger corrective workflows instantly through conversational requests.
Customer Impact
AI Network Empowerment
Challenge: A multi-network platform operator's support team of five had limited networking expertise, relying heavily on a single engineer for configuration and troubleshooting.
Solution: Deploying the swXtch.io AI Native Network introduced intelligent observability, guided automation, and contextual diagnostics - enabling all engineers to manage network operations confidently.
Results: The team gained full operational autonomy, improved fault response times, and reduced dependency on specialized skill sets.
