Practical examples showing enzu's value for everyday tasks — with budget control.
enzu shines when you need:
- Quick, structured outputs from LLMs
- Budget control to avoid runaway costs
- Simple integration without complex setup
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.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.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.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
| Without enzu | With enzu |
|---|---|
| No spending control | Set token/cost limits |
| Surprise bills | Predictable costs |
| Raw API complexity | Simple interface |
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
Need to process large documents that exceed context limits? See:
../production/— Full production pipelines with RLM