usecases

Use Cases

Practical examples showing enzu's value for everyday tasks — with budget control.

The Pattern

enzu shines when you need:

• Quick, structured outputs from LLMs
• Budget control to avoid runaway costs
• Simple integration without complex setup

Examples

Email Writer

email_writer.py — Generate professional emails with tone control

result = client.run(
    "Write a polite follow-up email about the project deadline",
    tokens=200,
)

Who needs this: Anyone who writes emails daily

---

Code Reviewer

code_reviewer.py — Get quick feedback on code snippets

result = client.run(
    f"Review this function for bugs and improvements:\n{code}",
    tokens=300,
)

Who needs this: Developers wanting a second opinion

---

Text Summarizer

text_summarizer.py — Condense articles or documents

result = client.run(
    f"Summarize in 3 bullet points:\n{article}",
    tokens=150,
)

Who needs this: Anyone drowning in content to read

---

Data Extractor

data_extractor.py — Pull structured data from unstructured text

result = client.run(
    f"Extract name, email, and company from:\n{text}",
    tokens=100,
)

Who needs this: Anyone processing forms, emails, or documents

---

Why enzu?

Without enzu	With enzu
No spending control	Set token/cost limits
Surprise bills	Predictable costs
Raw API complexity	Simple interface

Cost

Each example includes cost tracking. Typical costs:

• Email generation: ~$0.001-0.003
• Code review: ~$0.002-0.005
• Summarization: ~$0.001-0.002
• Data extraction: ~$0.001-0.002

For Large Content

Need to process large documents that exceed context limits? See:

• ../production/ — Full production pipelines with RLM