> ## Documentation Index
> Fetch the complete documentation index at: https://docs.qwedai.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Frequently asked questions

> Get answers to common questions about QWED verification. Learn how it differs from RAG, fine-tuning, and guardrails for deterministic LLM output validation.

## General

### What is QWED?

QWED is a deterministic verification protocol for Large Language Models (LLMs). It treats LLMs as "untrusted translators" and verifies their outputs using formal methods (SymPy, Z3, AST, SQLGlot).

### How is QWED different from other LLM tools?

| Feature                   | QWED        | RAG           | Fine-tuning | Guardrails |
| ------------------------- | ----------- | ------------- | ----------- | ---------- |
| **Deterministic**         | ✅ Yes       | ❌ No          | ❌ No        | ❌ No       |
| **Mathematically proven** | ✅ Yes       | ❌ No          | ❌ No        | ⚠️ Limited |
| **No training required**  | ✅ Yes       | ⚠️ Needs docs | ❌ No        | ✅ Yes      |
| **Works offline**         | ❌ API-based | ✅ Yes         | ✅ Yes       | ✅ Yes      |

**QWED complements these tools** — use RAG for knowledge, QWED for verification.

### Do I need to run `qwed init` every time?

No. Once initialized, QWED reads your provider credentials and configuration from the `.env` file that `qwed init` creates. You only need to re-run it when you want to switch LLM providers or rotate API keys. Running `qwed init` again merges new values into your existing `.env` — it does not overwrite settings you don't change.

***

## Integration

### Do I need to run a backend server?

**Yes.** QWED requires a backend server with your LLM API keys configured.

**Architecture:**

```
Your app → SDK → Backend server (you run) → LLM (your key) → Verifiers
```

**Setup:**

```bash theme={null}
# Step 1: Configure your LLM
cp .env.example .env
echo "ANTHROPIC_API_KEY=sk-ant-..." >> .env

# Step 2: Run backend
python -m qwed_api

# Step 3: Use SDK
python your_app.py
```

See [Getting started](./integration/getting-started) for full setup.

### Do I need to call my LLM first?

**No.** This is a common mistake.

❌ **Wrong:**

```python theme={null}
llm_result = openai.chat(...)  # Don't do this
qwed.verify(llm_result)  # Too late
```

✅ **Correct:**

```python theme={null}
# Let QWED backend handle LLM call
result = qwed.verify("your question")
```

The backend server (that you run) calls the LLM using your API key.

### What LLM providers does QWED support?

You configure your LLM provider in the backend's `.env` file:

**Supported providers:**

* OpenAI (direct API)
* Anthropic Claude
* Azure OpenAI
* AWS Bedrock
* Google Gemini

**Example `.env`:**

```bash theme={null}
ACTIVE_PROVIDER=anthropic
ANTHROPIC_API_KEY=sk-ant-...
```

See [LLM configuration](https://github.com/QWED-AI/qwed-verification/blob/main/docs/LLM_CONFIGURATION.md) for all providers.

### Can I use my own LLM API key?

**Yes.** You must use your own LLM API key. QWED is open source — you run the backend server with your credentials.

**You provide:**

* Your own LLM API key (in `.env`)
* Your own backend server (run locally)

**You control:**

* Which LLM provider to use
* All your data and keys

***

## Costs

### How much does QWED cost?

**Open source:** free.

* You pay only for your own LLM API usage
* No QWED subscription needed
* Run backend server yourself

**Costs you pay:**

* Your LLM provider (OpenAI, Anthropic, etc)
* Your hosting (if deploying backend)

**Example:**
If using Anthropic Claude:

* Input: \$3 per million tokens
* Output: \$15 per million tokens
* (See your LLM provider's pricing)

### What are my rate limits?

**QWED itself:** no rate limits. It's open source.

**Your LLM provider:** Check their limits:

* OpenAI: Tier-based (see dashboard)
* Anthropic: Based on plan
* Azure: Based on deployment

If you hit your LLM provider's rate limit, implement retries:

```python theme={null}
import time

try:
    result = qwed.verify(query)
except Exception as e:
    if "rate_limit" in str(e):
        time.sleep(60)  # Wait and retry
        result = qwed.verify(query)
```

***

## Security

### Is my data secure?

**Yes.** QWED:

* Uses encrypted connections (HTTPS/TLS)
* Doesn't store verification queries by default
* SOC 2 Type II compliant (Enterprise plan)
* Supports on-premise deployment (Enterprise Pro+)

### Can QWED access my database/files?

**No.** QWED only sees:

* The query you send
* SQL schema (if verifying SQL)
* Code snippet (if verifying code)

It cannot access your application database or files.

### How long is data retained?

**Default:** 30 days for audit logs\
**Enterprise:** Configurable (90 days - 7 years)\
**On-premise:** You control retention

***

## Performance

### How fast is QWED?

**Average response times:**

* Simple queries: 1-2 seconds
* Complex queries: 2-5 seconds
* Batch processing: 0.5s per item

**Factors affecting speed:**

* Query complexity
* Network latency
* Verification engine used

### Can I make QWED faster?

**Yes:**

1. **Use batch processing:**
   ```python theme={null}
   results = qwed.verify_batch(items)  # Faster than individual calls
   ```

2. **Cache results:**
   ```python theme={null}
   @cache
   def cached_verify(query):
       return qwed.verify(query)
   ```

3. **Use async:**
   ```python theme={null}
   results = await qwed.verify_async(queries)
   ```

***

## Verification domains

### What can QWED verify?

**Supported domains:**

1. **Math** - Calculations, equations, algebra
2. **Logic** - Propositional logic, SAT/UNSAT
3. **Code** - Security vulnerabilities, syntax
4. **SQL** - Injection attacks, tautologies
5. **Facts** - Multi-source consensus
6. **Stats** - Statistical claims
7. **Images** - Visual verification
8. **Consensus** - Multi-model agreement

### What can't QWED verify?

**Not supported:**

* Creative writing quality
* Subjective opinions
* Future predictions
* Unstructured text summaries

**Use cases:** QWED is for **objective, verifiable claims** only.

***

## Errors and debugging

### Why is my verification failing?

**Common causes:**

1. **Malformed input:**
   ```python theme={null}
   # ❌ Too vague
   result = qwed.verify("calculate something")

   # ✅ Specific
   result = qwed.verify("Calculate 15% of 200")
   ```

2. **Wrong verification method:**
   ```python theme={null}
   # ❌ Wrong
   result = qwed.verify(code_snippet)

   # ✅ Correct
   result = qwed.verify_code(code_snippet, language="python")
   ```

3. **Network issues:**
   ```python theme={null}
   result = qwed.verify(query, timeout=60)  # Increase timeout
   ```

### How do I debug verification failures?

**Enable verbose mode:**

```python theme={null}
client = QWEDClient(api_key="...", verbose=True)
result = client.verify("2+2=4")
# Prints internal flow to console
```

**Check trace:**

```python theme={null}
result = client.verify("2+2=4", return_trace=True)
print(result.trace)
# Shows LLM extraction → verification steps
```

***

## Production deployment

### Is QWED production-ready?

**Yes.** QWED is used in production by:

* Financial institutions (loan calculations)
* Healthcare AI (drug interaction checking)
* Legal tech (contract analysis)
* EdTech (student assessment)

### How do I deploy QWED to production?

See [Production deployment guide](/integration/production) for full checklist.

**Quick steps:**

1. Test thoroughly in staging
2. Deploy with feature flag
3. Start with 5% traffic (canary)
4. Monitor metrics
5. Gradually increase to 100%

### What if QWED goes down?

**Recommended:**

1. Implement fallback mechanism
2. Cache recent results
3. Graceful degradation

```python theme={null}
try:
    result = qwed.verify(query, timeout=5)
except QWEDError:
    # Fallback to cached/approximate result
    logger.warning("QWED unavailable, using fallback")
    return fallback_result()
```

***

## Support

### How do I get help?

**Community (free):**

* 📖 [Documentation](https://docs.qwedai.com)
* 💬 [GitHub Discussions](https://github.com/QWED-AI/qwed-verification/discussions)
* 🐛 [Report Bugs](https://github.com/QWED-AI/qwed-verification/issues)

**Enterprise support:**

* 📧 Email: [support@qwedai.com](mailto:support@qwedai.com)
* 💼 Slack Connect (Enterprise customers)
* 📞 Emergency Hotline (Enterprise Pro+)

**Response times:**

* Community: Best effort
* Pro: 24-48 hours
* Enterprise: 4-hour SLA
* Enterprise Pro+: 1-hour SLA

### Can I request new features?

**Yes.** Submit feature requests:

* GitHub: [https://github.com/QWED-AI/qwed-verification/issues](https://github.com/QWED-AI/qwed-verification/issues)
* Email: [support@qwedai.com](mailto:support@qwedai.com)

**Most requested features:**

* Real-time streaming verification (Q2 2026)
* Client-side verification (Q3 2026)
* More language SDKs (ongoing)

***

## Still have questions?

* 📖 [Full documentation](https://docs.qwedai.com)
* 💬 [Community forum](https://github.com/QWED-AI/qwed-verification/discussions)
* 📧 Contact: [support@qwedai.com](mailto:support@qwedai.com)