Reference Applications
Examples built with K9-AIF
Practical demos showing how K9-AIF structures routing, orchestration, squads, agents,
model abstraction, and domain workflows in real AI applications.
These examples show how the K9-AIF Framework can be applied to practical,
domain-oriented AI systems while preserving architectural structure, modularity, and governance.
Together, they demonstrate how K9-AIF uses stable Architecture Building Blocks (ABB)
to host configurable Solution Building Blocks (SBB), including routing,
orchestration, squads, agent behaviors, model abstraction, and domain workflows.
An enterprise-style support workflow example built on the K9-AIF Framework.
ACME Support Center demonstrates how K9-AIF can structure a customer-facing support system
using specialized agents, configurable reasoning behaviors, and stable framework architecture.
- Router → Orchestrator → Squad → Agent execution flow
- ModelRouterFactory usage for inference abstraction
- Configurable reasoning patterns such as ReAct, Agentic RAG, Plan & Execute, Reflection, and multi-agent collaboration
- Clear separation between Architecture Building Blocks (ABB) and Solution Building Blocks (SBB)
- Squad-based specialization across support roles
- Runtime logging and observability through K9-AIF framework logging
This example is a strong reference implementation of how K9-AIF can support modular,
enterprise-oriented multi-agent service architectures.
A lightweight browser-based chat example built on the K9-AIF Framework.
K9Chat demonstrates how a simple chat experience can be implemented using K9-AIF building
blocks while remaining configuration-driven and model-provider agnostic.
- Squad + Agent execution pattern
- ModelRouterFactory usage for inference abstraction
- Default K9ModelRouter routing behavior
- Integration with configurable LLM providers such as Ollama
- Default SQLite-backed router state persistence
- Browser-based interaction with runtime metadata display
This example serves as a clean starting point for understanding how K9-AIF separates agent
logic, routing, inference configuration, persistence, and UI integration.
A domain-oriented example showing how K9-AIF can support structured, document-heavy,
workflow-driven enterprise scenarios.
- Claims-related workflow structure
- Intake and document-processing patterns
- Domain-specific orchestration
- Extensible enterprise solution design aligned to real business processes
- Modular AI solution composition using K9-AIF concepts
This example reflects how K9-AIF can be applied in business domains where architecture,
modularity, and workflow structure matter more than a single prompt-response interaction.
How to run the examples
From the root of the k9-aif-framework repository, the included shell scripts can be
used to quickly launch selected examples.
./run_k9chat.sh
./run_model_router.sh
./run_acme_support_center.sh
For deeper implementation details, class diagrams, and example-specific documentation,
use the links above to open the corresponding example folders in the repository.
These examples are intentionally practical. They are not intended to be full production products
out of the box, but to demonstrate how K9-AIF can be used as an
architecture-first framework for building modular, governed, and extensible AI applications.