# SEO Audit: A3M Router (adaptive-memory-multi-model-router)

**Date:** 2026-05-18 (Updated)
**Package:** adaptive-memory-multi-model-router
**NPM URL:** https://www.npmjs.com/package/adaptive-memory-multi-model-router
**GitHub URL:** https://github.com/Das-rebel/a3m-router

---

## 1. Keyword Research

### Primary Keywords (benchmark-driven, high intent)

| Keyword | Est. Monthly Volume | Competition | Intent | Priority |
|---------|---------------------|-------------|--------|----------|
| `llm router benchmark` | 1,200-2,000 | Low | Commercial | P0 |
| `llm routing accuracy` | 800-1,500 | Low | Informational | P0 |
| `routellm alternative` | 1,500-3,000 | Low-Medium | Commercial | P0 |
| `litellm alternative` | 1,500-3,000 | Low-Medium | Commercial | P0 |
| `llm cost optimization` | 800-1,500 | Low | Commercial | P0 |
| `openai proxy free` | 2,000-4,000 | Medium | Transactional | P0 |
| `llm gateway open source` | 1,000-2,000 | Low-Medium | Commercial | P0 |

### Long-Tail Keywords (FAQ/content targets)

| Keyword | Est. Monthly Volume | Competition | Intent | Priority |
|---------|---------------------|-------------|--------|----------|
| `how to reduce openai api costs` | 1,500-3,000 | Low | Informational | P0 |
| `llm routing without gpu` | 300-600 | Very Low | Informational | P0 |
| `lightweight llm router` | 500-1,000 | Low | Commercial | P0 |
| `keyword-based llm routing` | 100-300 | Very Low | Informational | P1 |
| `drop-in openai proxy` | 300-600 | Low | Commercial | P0 |
| `free llm proxy` | 800-1,500 | Low | Transactional | P0 |
| `cheapest openai api alternative` | 500-1,000 | Low | Commercial | P0 |

### Competitive/Comparison Keywords (HIGH VALUE)

| Keyword | Est. Monthly Volume | Competition | Priority |
|---------|---------------------|-------------|----------|
| `routellm alternative` | 1,500-3,000 | Low-Medium | P0 |
| `litellm alternative` | 1,500-3,000 | Low-Medium | P0 |
| `a3m router vs litellm` | 50-100 | Very Low | P1 |
| `a3m router vs routellm` | 50-100 | Very Low | P1 |
| `openrouter alternative` | 200-400 | Low | P1 |
| `portkey alternative` | 100-200 | Very Low | P2 |

### Secondary Keywords

| Keyword | Est. Monthly Volume | Competition | Priority |
|---------|---------------------|-------------|----------|
| `ai gateway` | 5,000-8,000 | High | P1 |
| `model routing` | 500-1,000 | Low | P1 |
| `llm proxy` | 1,000-2,000 | Low-Medium | P1 |
| `openai compatible proxy` | 500-1,000 | Low | P1 |
| `llm load balancer` | 300-800 | Low | P1 |
| `llm provider comparison` | 1,000-2,000 | Medium | P1 |

---

## 2. Key Messages (use everywhere)

1. **"82.5% routing accuracy without ML"** — Lead metric, differentiator
2. **"Matches RouteLLM BERT within 2.5%"** — Competitive positioning
3. **"30x more efficient than GPU-based routing"** — Efficiency story
4. **"Only router besides RouteLLM with published benchmarks"** — Trust signal
5. **"245% growth, 2,775 downloads in 3 days"** — Social proof

---

## 3. Competitive Positioning

### RouteLLM Alternative (HIGH VALUE)

"RouteLLM alternative" is our highest-value keyword because:
- RouteLLM users are actively looking for alternatives (GPU cost, complexity)
- We have a direct benchmark comparison (within 2.5%)
- We offer features RouteLLM lacks (proxy, cache, guardrails)

**Positioning:** "A3M Router matches RouteLLM BERT within 2.5% — without GPU. Plus proxy, cache, guardrails."

### LiteLLM Alternative (HIGH VALUE)

"LiteLLM alternative" captures users who want:
- Published routing benchmarks
- Zero-config setup
- Built-in semantic caching

**Positioning:** "A3M Router is the only LiteLLM alternative with published routing benchmarks (82.5% accuracy)."

### Competitive Table

| Competitor | NPM Weekly Downloads | Our Edge |
|------------|---------------------|----------|
| litellm | ~80,000 | Published benchmarks, zero-config, semantic cache |
| openrouter-sdk | ~5,000 | Self-hosted, no middleman fees, published accuracy |
| portkey-ai | ~3,000 | Open-source, free, no signup, benchmarks |
| routellm | ~1,000 | No GPU needed, proxy included, 39 providers |

---

## 4. On-Page SEO Checklist

### docs-site/index.html

| Element | Status | Target |
|---------|--------|--------|
| Title tag | UPDATED | "A3M Router — 82.5% Routing Accuracy Without ML \| Matches RouteLLM" |
| Meta description | UPDATED | 30x efficiency story with accuracy metric |
| Keywords meta | UPDATED | All 12 primary/long-tail keywords |
| H1 tag | UPDATED | "LLM Routing That Matches GPU Models — Without GPU" |
| Stats section | UPDATED | Leads with 82.5% accuracy, 2.5% gap, 30x efficiency |
| FAQ schema | UPDATED | 8 questions targeting AI search queries |
| OG tags | UPDATED | Benchmark-first messaging |
| Twitter cards | UPDATED | Benchmark-first messaging |

### Content Structure (H-tag hierarchy)

```
H1: LLM Routing That Matches GPU Models — Without GPU
H2: Intelligent LLM Routing (feature)
H2: Cost Optimization (feature)
H2: Smart Fallback & Retry (feature)
H2: Real-time Analytics (feature)
H2: Security Guardrails (feature)
H2: Semantic Cache (feature)
H2: LLM Provider Pricing Tiers (section)
H3: Free/Budget/Mid/Premium Tier
H2: Quick Start: LLM Routing in 30 Seconds
H2: Frequently Asked Questions
H3: What is LLM routing accuracy?
H3: How does keyword-based routing compare to ML routing?
H3: What is the best lightweight LLM router?
H3: How to reduce OpenAI API costs?
H3: How does A3M Router compare to RouteLLM?
H3: How does A3M Router compare to LiteLLM?
```

---

## 5. Technical SEO

### robots.txt (UPDATED)
- Allows full crawling
- Explicitly allows docs/, assets/, llms.txt, README.md
- Sitemap reference included
- Blocks /node_modules/, /dist/, /test/, /src/, /.git/

### sitemap.xml (UPDATED)
- 11 URLs including all key pages
- New: GEO.md, SEO_AUDIT.md, CONFIGURATION.md, INTEGRATIONS.md, benchmark-results.json, llms.txt
- Priority weighting: homepage (1.0) > GitHub (0.9) > NPM (0.9) > docs (0.7-0.8)

### llms.txt (UPDATED)
- Leads with benchmark story (82.5% accuracy)
- Includes comparison table vs RouteLLM/LiteLLM
- Structured data section for AI extraction
- All 5 key messages included

---

## 6. GEO (Generative Engine Optimization)

See `docs/GEO.md` for full GEO strategy. Key elements:

1. **FAQ format** answering AI-searchable questions
2. **Comparison tables** with verifiable data AI engines cite
3. **Structured key-value block** for direct AI extraction
4. **Target AI queries** mapped to A3M Router answers

---

## 7. Action Items

- [x] Update docs-site/index.html title, meta, H1, stats, FAQ
- [x] Update FAQ schema with benchmark-focused questions
- [x] Update OG/Twitter cards with benchmark messaging
- [x] Update llms.txt with benchmark story
- [x] Create docs/GEO.md with AI search optimization
- [x] Update docs/SEO_AUDIT.md with new keywords
- [x] Update public/sitemap.xml with all key pages
- [x] Update public/robots.txt with better crawling rules
- [x] Update package.json keywords (optimized)
- [ ] Create OG banner image with benchmark metrics
- [ ] Write comparison articles (A3M vs RouteLLM, vs LiteLLM)
- [ ] Submit sitemap to Google Search Console
- [ ] Set up Google Search Console for das-rebel.github.io
