Reference repository for production-oriented AI automation patterns used in business workflows.
This repository packages repeatable case studies around support operations, document intake, reporting, and internal knowledge workflows. The goal is not to ship a single product, but to show how practical AI systems can be scoped, instrumented, and delivered with lightweight infrastructure.
Teams often understand what they want from AI in broad terms, but not how to turn it into a workflow that is observable, testable, and maintainable. These case studies provide reusable blueprints with business context, architecture, rollout notes, and operational constraints.
- Support automation for ticket triage, summarization, and draft replies
- Document intake workflows for extraction, validation, and human review
- Revenue and operations reporting copilots for internal teams
- Knowledge assistants for policy and process lookup
flowchart LR
A["Business Trigger"] --> B["Ingestion Layer"]
B --> C["AI Task Router"]
C --> D["LLM / Extraction / Retrieval"]
D --> E["Validation + Rules"]
E --> F["Human Review (Optional)"]
F --> G["System of Record / Output"]
E --> G
G --> H["Metrics + Evaluation"]
cases/contains business case studies with delivery notes and rollout strategycatalog.jsonprovides a machine-readable index used by CI validationscripts/validate_catalog.pyvalidates consistency between the index and markdown content
python -m unittest discover -s tests
python scripts/validate_catalog.py- Add procurement workflow and lead qualification patterns
- Publish rollout checklists for low-risk pilot launches
- Extend the catalog with architecture variants by team size