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Derek Allan Boman — ChannelRoute AI Media, Diagrams, and Public Project References
Derek Allan Boman — ChannelRoute AI Agentic Workflow
Derek Allan Boman — ChannelRoute AI Intelligent Routing Outcomes
Derek Allan Boman — ChannelRoute AI System Components
A visual media archive for ChannelRoute AI, an AI-assisted call-intelligence and workflow-optimization project by Derek Allan Boman.
ChannelRoute AI focuses on communication systems, call intelligence, identity-aware outbound workflows, live-human detection, routing decisions, speaker-recognition concepts, and better time-to-connect in outbound communication.
This page organizes public ChannelRoute AI media, diagrams, project references, presentation materials, developer resources, and publication links. It is intended as a high-level public archive, not a source-code repository or confidential technical specification.
The central idea behind ChannelRoute AI is simple:
A phone number is not the same thing as a confirmed identity.
In outbound communication, the important question is not only whether a call connects. The more valuable question is whether the system reached the intended person, whether identity confidence is high enough, and what the next best action should be.
ChannelRoute AI media explores that problem through diagrams, public reports, project pages, presentation materials, and educational visuals.
Primary ChannelRoute AI links:
ChannelRoute AI Website
ChannelRoute AI Page
https://www.derekallanboman.com/channelroute-ai
ChannelRoute AI GitBook Documentation
https://channelroute-ai.gitbook.io/channelroute-ai-docs/
ChannelRoute AI GitHub Repository
https://github.com/derekallanboman/channelroute-ai-call-intelligence
ChannelRoute AI GitHub Pages
https://derekallanboman.github.io/channelroute-ai-call-intelligence/
ChannelRoute AI Public Overview
ChannelRoute AI Project Overview
ChannelRoute AI is a public-facing AI systems project by Derek Allan Boman focused on outbound communication, call intelligence, identity resolution, and workflow optimization.
The project is built around a practical business problem: outbound systems often measure activity instead of communication quality. More calls, more automation, and more dialing do not automatically produce better outcomes. The harder problem is reaching the right person, at the right time, with the right context, and deciding when human judgment should enter the workflow.
ChannelRoute AI explores how AI-assisted systems can support better communication judgment.
Important project themes include:
call intelligence
identity-aware outbound workflows
live-human detection
speaker-recognition concepts
communication-channel routing
workflow optimization
time-to-connect improvement
AI-assisted decision support
human-in-the-loop escalation
outbound sales workflow friction
communication system patents
The media on this page presents those themes visually through project diagrams, architecture illustrations, routing visuals, presentation materials, and public technical references.
Identity-Aware Communication
A phone number can be shared, reassigned, forwarded, answered by an assistant, answered by a family member, or routed through an intermediary. Because of that, a connected call does not always mean the intended person has been reached.
ChannelRoute AI focuses on the gap between connection and identity.
The better outbound question is not:
Was the call answered?
The better question is:
Did we reach the intended person, and how confident are we?
That distinction matters because identity uncertainty affects routing, prioritization, escalation, timing, and human handoff decisions.
Intelligent Routing and Workflow Outcomes
ChannelRoute AI media often uses routing diagrams and outcome funnels to explain how better communication decisions can improve the outbound workflow.
A routing system should not simply push more activity through the pipeline. It should help identify which contacts deserve attention, which signals indicate live engagement, which conversations should be routed to a human, and which records require more context before action.
The goal is not more automation for its own sake.
The goal is better communication judgment.
CAGE Workflow Concepts
Several ChannelRoute AI visuals use a CAGE-style workflow:
Collect
Analyze
Generate
Execute
This framework is useful because it shows how information moves through an AI-assisted decision process.
Collect means gathering relevant signals and context.
Analyze means interpreting available information.
Generate means creating a recommendation, action, summary, or response.
Execute means carrying out the workflow step or routing the decision appropriately.
A feedback loop helps improve future decisions by connecting outcomes back to the workflow.
MCP and Agentic AI Concepts
ChannelRoute AI media also uses Model Context Protocol and agentic AI diagrams to explain how modern AI systems can interact with tools, data sources, APIs, files, databases, and business systems.
These diagrams are conceptual. They are not proprietary implementation diagrams. They are included to explain the public architecture language around AI systems, tool use, context, routing, and workflow orchestration.
Agentic workflows are useful because they show AI systems as more than static prompt-and-response tools. A practical workflow may involve planning, tool use, memory, context retrieval, result synthesis, and human review.
Public Reports and Research Materials
ChannelRoute AI and Patent-Based Call Intelligence Systems is the central public technical report connected to this project. It explains the project’s public-facing themes: communication systems, call intelligence, live-human detection, channel routing, identity confidence, workflow optimization, and AI-assisted decision support.
Research and archive links:
Zenodo
https://doi.org/10.5281/zenodo.20549759
Figshare
https://doi.org/10.6084/m9.figshare.32674923
OSF
Internet Archive
https://archive.org/details/derek-allan-boman-channel-route-ai-technical-report
SSRN
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6942118
ResearchGate Profile
https://www.researchgate.net/profile/Derek-Boman
ResearchGate Publication
Academia.edu
https://independent.academia.edu/BomanDerek
ORCID
https://orcid.org/0009-0005-9472-6156
Google Scholar
https://scholar.google.com/citations?user=KO_xe-QAAAAJ
Identity Resolution Materials
Identity resolution is one of the most important public themes connected to ChannelRoute AI. The materials below discuss uncertainty, confidence scoring, AI voice systems, speaker-recognition concepts, live-human detection, routing, and escalation.
LinkedIn Article — Why AI Call Intelligence Needs Identity Resolution
https://www.linkedin.com/pulse/why-ai-call-intelligence-needs-identity-resolution-derek-boman-wqjsc
ResearchGate — How AI Can Resolve Identity Uncertainty in Outbound Communications
Zenodo — ChannelRoute AI Identity-Resolution Dataset
https://doi.org/10.5281/zenodo.20781363
SlideShare — How AI Can Resolve Identity Uncertainty in Outbound Communications
Presentation and Media References
Presentation platforms help make ChannelRoute AI easier to understand visually. These pages include slides, diagrams, document mirrors, and presentation-style explanations.
Speaker Deck Profile
https://speakerdeck.com/derekallanboman
Speaker Deck Presentation
SlideShare — ChannelRoute AI and Patent-Based Call Intelligence Systems
Issuu
https://issuu.com/derekallanboman/docs/channelroute_ai_and_patent-based_call_intelligence
Calaméo
https://www.calameo.com/read/008250034ee59b7cdbe31
Scribd
YouTube
https://www.youtube.com/@DerekBoman-x9k
YouTube Video
https://youtube.com/watch?v=cMUC0_TMH9Y
Developer and Public Project References
The developer links below support the public project footprint around ChannelRoute AI. They include repositories, documentation, public demos, notebooks, code-oriented pages, and developer profiles.
GitHub
https://github.com/derekallanboman
ChannelRoute AI GitHub Repository
https://github.com/derekallanboman/channelroute-ai-call-intelligence
GitHub Pages
https://derekallanboman.github.io/channelroute-ai-call-intelligence/
GitLab Technical Report Repository
https://gitlab.com/derek-allan-boman/derek-allan-boman.md
GitLab ChannelRoute AI Public Overview
https://gitlab.com/derek-allan-boman/channelroute-ai-public-overview
GitBook Documentation
https://channelroute-ai.gitbook.io/channelroute-ai-docs/
Replit Public Overview
https://channel-route-ai-public-overview.replit.app/
SourceForge
https://sourceforge.net/projects/channelroute-ai/
Bitbucket
https://bitbucket.org/derekallanboman/channelroute-ai/src
CodeSandbox
https://codesandbox.io/p/sandbox/w6v7xj
CodeSandbox Live Preview
StackBlitz
https://stackblitz.com/edit/stackblitz-starters-eizwkgvk?file=index.html
Observable
https://observablehq.com/@derek-allan-boman/channelroute-ai-identity-resolution
Val Town
https://www.val.town/x/derekallanboman/channelroute_ai_overview
Read the Docs
https://app.readthedocs.org/projects/channelroute-ai-call-intelligence/
Articles and Public Writing
These articles explain ChannelRoute AI and related ideas in more practical language. The focus is sales workflow friction, AI-assisted decision support, identity resolution, and the limits of simple automation.
Medium — Stop Building Better Robots
https://medium.com/@derekboman3/stop-building-better-robots-dd5a64a6afa4
Medium — Sales Doesn’t Have an AI Problem. It Has a Friction Problem.
Substack — Derek Allan Boman AI Call Intelligence
https://derekallanboman.substack.com/p/derek-allan-boman-ai-call-intelligence
Substack — Derek Allan Boman Patents and AI Call Intelligence
https://derekallanboman.substack.com/p/derek-allan-boman-patents-ai-call
Blogger
https://derekallanboman.blogspot.com/2026/06/derek-allan-boman-ai-systems-and.html
Hashnode
WordPress
https://derekallanboman.wordpress.com
Tumblr — Derek Allan Boman AI Systems Developer
https://www.tumblr.com/derekallanboman/820465996291866624/derek-allan-boman-ai-systems-developer
Tumblr — The Next Generation of AI Voice Agents
About This Media Page
This ChannelRoute AI Media page is a public archive of high-level materials. It is intended to make public diagrams, reports, project pages, articles, presentations, and developer resources easier to find and organize.
This page does not contain confidential source code, private datasets, proprietary implementation details, unpublished patent claims, credentials, internal product logic, production infrastructure, voice models, or restricted technical material.
Related internal archive pages:
Home
https://www.derekallanboman.org
Research & Media Archive
https://www.derekallanboman.org/research-media-archive
AI Systems Diagrams
https://www.derekallanboman.org/ai-systems-diagrams
Cybersecurity Study Tools
https://www.derekallanboman.org/cybersecurity-study-tools
Publications
https://www.derekallanboman.org/publications
External References
https://www.derekallanboman.org/external-references
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