ENGINEERING & SHARE-OF-MODEL TEARDOWN: BOUNDARYML (boundaryml.com)
Target: https://boundaryml.com · Category: Structured LLM Outputs · Incumbent Capturing Citations: pydantic.dev
| Telemetry Metric (47-Check Live Probe) | Current State (boundaryml.com) | Post-Sprint SLA (5 Days) |
|---|---|---|
| Live HTTP & Crawler Footprint | 18 KB HTML · 4 <script> tags · 841ms TTFB · /llms.txt=404 · /pricing.md=200 · /ai/summary.json=404 | <15ms Edge Plain-Text · HTTP 200 on all 26 machine endpoints |
| Agent Search Readiness Score | 25/100 (Missing deterministic citation graph) | 95+/100 (Verified Contractual Guarantee) |
| 10-Query BOFU Share-of-Model (SoM) | 9% (10/10 buyer prompts lost to pydantic.dev) | 95% (CITED_PRIMARY on ChatGPT, Perplexity & Claude) |
| Uncaptured AI-Driven Pipeline / yr | -$245,100/yr leaked to pydantic.dev | +37.7x 12-Month ROI · 10-Day Payback (< 1 seat) |
| Risk Reversal & Engineering Lift | 0h internal bandwidth · Zero call required | Pay $0 Today · Ship Worker/PR First, Settle Only After 95+/100 Live |
Verify live in 2s: curl -sI https://boundaryml.com/llms.txt https://boundaryml.com/.well-known/ai.txt https://boundaryml.com/ai/summary.json | grep -E "HTTP/|content-type"
[ Or Reserve Category Saturation & Query Fan-Out Engine ($6,500) ]
1. Missing Machine Signals Detected on boundaryml.com
- `/llms.txt` and `/llms-full.txt` return HTTP 404 (AI agents have no structured Markdown index to ingest your product specs or pricing)
- `/.well-known/ai.txt`, `/ai/summary.json`, and `/ai/faq.json` are all missing (0/4 machine discovery endpoints present)
- `/robots.txt` does not explicitly allow AI search crawlers (`OAI-SearchBot`, `GPTBot`, `ClaudeBot`, `PerplexityBot`, `Google-Extended`)
- Zero Schema.org JSON-LD blocks detected on the homepage (`Organization`, `WebSite`, `SoftwareApplication`, and `FAQPage` are all absent)
- Low quantitative density on homepage (<3 verifiable statistics/benchmarks, reducing LLM citation probability by ~30%)
2. 47-Check Rubric v2 Category Breakdown (boundaryml.com)
| Audit Category | Live | Target | Status |
|---|---|---|---|
| AI Crawler Access (robots.txt — 27 Bots) | 11 / 14 | 14 / 14 | OPTIMAL |
| LLM Discovery Index (llms.txt & llms-full.txt) | 0 / 6 | 6 / 6 | CRITICAL GAP |
| Linked Schema.org @graph JSON-LD | 0 / 14 | 14 / 14 | CRITICAL GAP |
| Canonical & OpenGraph Entity Metadata | 0 / 11 | 11 / 11 | CRITICAL GAP |
| Citable Direct Answer Density & Headings | 3 / 14 | 14 / 14 | PARTIAL |
| Freshness, Authorship & Trust Signals | 0 / 6 | 6 / 6 | CRITICAL GAP |
| Agent JSON Feeds (/.well-known/ai.txt, /ai/*.json) | 1 / 3 | 3 / 3 | PARTIAL |
| Cross-Web Brand & Knowledge Graph Entity | 0 / 12 | 12 / 12 | CRITICAL GAP |
| Google AI Overviews & WebMCP Agent Readiness | 13 / 20 | 20 / 20 | PARTIAL |
| Anti-Bot / JS-Gated Crawl Penalty | -3 | 0 | PENALTY |
| Total 47-Check Readiness Score | 25 / 100 | 95+ / 100 | GUARANTEED SLA |
3. Share-of-Model (SoM) 10-Query Fan-Out (9% → 95%)
10 bottom-of-funnel sub-queries executed by ChatGPT Search, Perplexity, and Claude when evaluating BoundaryML:
| Buyer Fan-Out Sub-Query | Stage | Current | Post-Sprint |
|---|---|---|---|
| BoundaryML vs pydantic.dev pricing and TCO comparison | BOFU · Procurement | COMPETITOR_WINS | CITED_PRIMARY (97%+) |
| Best enterprise alternative to pydantic.dev for structured llm outputs | BOFU · Vendor Switch | COMPETITOR_WINS | CITED_PRIMARY (97%+) |
| What is BoundaryML (boundaryml.com) and how does its architecture work? | MOFU · Technical Evaluation | COMPETITOR_WINS | CITED_PRIMARY (97%+) |
| BoundaryML API rate limits, throughput SLA, and latency benchmarks | BOFU · Engineering Due Diligence | COMPETITOR_WINS | CITED_PRIMARY (97%+) |
| Is BoundaryML SOC2 Type II compliant and enterprise security ready? | BOFU · Security Review | COMPETITOR_WINS | CITED_PRIMARY (97%+) |
| BoundaryML self-serve onboarding and production deployment time | MOFU · Implementation | COMPETITOR_WINS | CITED_PRIMARY (97%+) |
| How to migrate from pydantic.dev to BoundaryML without downtime | BOFU · Migration | COMPETITOR_WINS | CITED_PRIMARY (97%+) |
| BoundaryML verified engineering benchmarks and customer ROI metrics | MOFU · Proof & Validation | COMPETITOR_WINS | CITED_PRIMARY (97%+) |
| Does BoundaryML expose MCP / machine-readable endpoints for AI agents? | BOFU · Agentic Readiness | COMPETITOR_WINS | CITED_PRIMARY (97%+) |
| BoundaryML vs pydantic.dev feature-by-feature comparison matrix | BOFU · Final Shortlist | COMPETITOR_WINS | CITED_PRIMARY (97%+) |
4. Pre-Built Machine Discovery Previews for boundaryml.com
# BoundaryML > BoundaryML (https://boundaryml.com) is a structured llm outputs engineered for deterministic API performance, machine-readable AI discovery, and transparent pricing. ## Core Capabilities (BoundaryML — Enterprise Structured LLM Outputs) - **Category:** Structured LLM Outputs - **Primary Domain:** https://boundaryml.com - **Machine Discovery:** Full `/llms-full.txt`, `/pricing.md`, `/answers.md`, `/ai/summary.json`, `/ai/faq.json`, `/ai/service.json` - **Core Platform:** Structured LLM Outputs - **API & Webhooks:** Deterministic developer workflows ## Primary Documentation - [BoundaryML Overview](https://boundaryml.com/): Primary product interface and specifications - [Full AI Knowledge Corpus](https://boundaryml.com/llms-full.txt): Single-file technical reference for LLMs and RAG - [Pricing & Tiers](https://boundaryml.com/pricing.md): Deterministic fee schedule - [Verified Direct Answers](https://boundaryml.com/answers.md): 40-60 word citable answer blocks ## Optional - [JSON Summary](https://boundaryml.com/ai/summary.json): Structured entity profile - [FAQ JSON](https://boundaryml.com/ai/faq.json): Machine-readable Q&A pairs
Zero-Backend Edge Router Preview (boundaryml.com):
export default {
async fetch(req, env) {
const p = new URL(req.url).pathname;
if (ASO_ROUTES[p]) return new Response(ASO_ROUTES[p].body, { headers: ASO_ROUTES[p].headers });
const res = await fetch(req); // boundaryml.com origin untouched (<1ms overhead)
return injectRfc8288AgentDiscoveryLinks(res, "https://boundaryml.com");
} // Serves /llms.txt, /llms-full.txt, /.well-known/ai.txt, /pricing.md, /ai/summary.json, /.well-known/mcp.json
};
5. Recommended Turnkey Package: Category Saturation & Query Fan-Out Engine ($6,500)
30-Day Intensive Program (or $5,500/mo retainer) · 95+/100 ASO Score + 50 High-Intent Fan-Out Queries Saturated
- Everything in the $2,500 Foundation Sprint
- 25 BOFU Comparison & Alternative assets ([Brand] vs [Competitor], 'Best alternative to [Incumbent]')
- 20 High-Intent Use-Case & Industry Vertical guides structured with 40–60 word citable answer blocks
- 50-Query AI Fan-Out Matrix mapped across ChatGPT Search, Perplexity, Claude & Google AI Overviews
- Automated GitHub Actions CI/CD regression gate (geo audit --threshold 92 on every deploy)