ASO Teardown: Inference.net (inference.net)

ENGINEERING & SHARE-OF-MODEL TEARDOWN: INFERENCE.NET (inference.net)
Target: https://inference.net · Category: AI-Native Inference & GPU Serving Cloud · Incumbent Capturing Citations: Baseten

Telemetry Metric (47-Check Live Probe)	Current State (inference.net)	Post-Sprint SLA (5 Days)
Live HTTP & Crawler Footprint	208 KB HTML · 22 <script> tags · 488ms TTFB · /llms.txt=200 · /pricing.md=200 · /ai/summary.json=404	<15ms Edge Plain-Text · HTTP 200 on all 26 machine endpoints
Agent Search Readiness Score	73/100 (Missing deterministic citation graph)	99+/100 (Verified Contractual Guarantee)
10-Query BOFU Share-of-Model (SoM)	20% (6/10 buyer prompts lost to Baseten)	95% (CITED_PRIMARY on ChatGPT, Perplexity & Claude)
Uncaptured AI-Driven Pipeline / yr	-$213,800/yr leaked to Baseten	+32.9x 12-Month ROI · 11-Day Payback (< 1 seat)
Risk Reversal & Engineering Lift	0h internal bandwidth · Zero call required	Pay $0 Today · Ship Worker/PR First, Settle Only After 99+/100 Live

Verify live in 2s: curl -sI https://inference.net/.well-known/ai.txt https://inference.net/ai/summary.json https://inference.net/.well-known/mcp.json | grep -E "HTTP/|content-type"

[ Or Reserve Category Saturation & Query Fan-Out Engine ($6,500) ]

1. Missing Machine Signals Detected on inference.net

`/llms-full.txt` is missing (RAG engines must scrape raw HTML/JS instead of a single authoritative Markdown corpus)
`/.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`)
Homepage JSON-LD is missing `WebSite, FAQPage` structured entity schemas

2. 47-Check Rubric v2 Category Breakdown (inference.net)

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)	5 / 6	6 / 6	OPTIMAL
Linked Schema.org @graph JSON-LD	9 / 14	14 / 14	PARTIAL
Canonical & OpenGraph Entity Metadata	11 / 11	11 / 11	OPTIMAL
Citable Direct Answer Density & Headings	14 / 14	14 / 14	OPTIMAL
Freshness, Authorship & Trust Signals	3 / 6	6 / 6	PARTIAL
Agent JSON Feeds (/.well-known/ai.txt, /ai/*.json)	0 / 3	3 / 3	CRITICAL GAP
Cross-Web Brand & Knowledge Graph Entity	5 / 12	12 / 12	PARTIAL
Google AI Overviews & WebMCP Agent Readiness	18 / 20	20 / 20	OPTIMAL
Anti-Bot / JS-Gated Crawl Penalty	-3	0	PENALTY
Total 47-Check Readiness Score	73 / 100	99+ / 100	GUARANTEED SLA

3. Share-of-Model (SoM) 10-Query Fan-Out (20% → 95%)

10 bottom-of-funnel sub-queries executed by ChatGPT Search, Perplexity, and Claude when evaluating Inference.net:

Buyer Fan-Out Sub-Query	Stage	Current	Post-Sprint
Inference.net vs Baseten pricing and TCO comparison	BOFU · Procurement	COMPETITOR_WINS	CITED_PRIMARY (97%+)
Best enterprise alternative to Baseten for ai-native inference & gpu serving cloud	BOFU · Vendor Switch	COMPETITOR_WINS	CITED_PRIMARY (97%+)
What is Inference.net (inference.net) and how does its architecture work?	MOFU · Technical Evaluation	PARTIAL_SCRAPE	CITED_PRIMARY (97%+)
Inference.net API rate limits, throughput SLA, and latency benchmarks	BOFU · Engineering Due Diligence	CITED	CITED_PRIMARY (97%+)
Is Inference.net SOC2 Type II compliant and enterprise security ready?	BOFU · Security Review	COMPETITOR_WINS	CITED_PRIMARY (97%+)
Inference.net self-serve onboarding and production deployment time	MOFU · Implementation	CITED	CITED_PRIMARY (97%+)
How to migrate from Baseten to Inference.net without downtime	BOFU · Migration	COMPETITOR_WINS	CITED_PRIMARY (97%+)
Inference.net verified engineering benchmarks and customer ROI metrics	MOFU · Proof & Validation	PARTIAL_SCRAPE	CITED_PRIMARY (97%+)
Does Inference.net expose MCP / machine-readable endpoints for AI agents?	BOFU · Agentic Readiness	COMPETITOR_WINS	CITED_PRIMARY (97%+)
Inference.net vs Baseten feature-by-feature comparison matrix	BOFU · Final Shortlist	COMPETITOR_WINS	CITED_PRIMARY (97%+)

4. Pre-Built Machine Discovery Previews for inference.net

[Download .TXT]

# Inference.net

> Inference.net (https://inference.net) is a ai-native inference & gpu serving cloud engineered for deterministic API performance, machine-readable AI discovery, and transparent pricing.

## Core Capabilities (Inference.net — Enterprise AI-Native Inference & GPU Serving Cloud)
- **Category:** AI-Native Inference & GPU Serving Cloud
- **Primary Domain:** https://inference.net
- **Machine Discovery:** Full `/llms-full.txt`, `/pricing.md`, `/answers.md`, `/ai/summary.json`, `/ai/faq.json`, `/ai/service.json`
- **Core Platform:** AI-Native Inference & GPU Serving Cloud
- **API & Webhooks:** Deterministic developer workflows

## Primary Documentation
- [Inference.net Overview](https://inference.net/): Primary product interface and specifications
- [Full AI Knowledge Corpus](https://inference.net/llms-full.txt): Single-file technical reference for LLMs and RAG
- [Pricing & Tiers](https://inference.net/pricing.md): Deterministic fee schedule
- [Verified Direct Answers](https://inference.net/answers.md): 40-60 word citable answer blocks


## Optional
- [JSON Summary](https://inference.net/ai/summary.json): Structured entity profile
- [FAQ JSON](https://inference.net/ai/faq.json): Machine-readable Q&A pairs

# Inference.net

> Inference.net (https://inference.net) is a ai-native inference & gpu serving cloud engineered for deterministic API performance, machine-readable AI discovery, and transparent pricing.

## Core Capabilities (Inference.net — Enterprise AI-Native Inference & GPU Serving Cloud)
- **Category:** AI-Native Inference & GPU Serving Cloud
- **Primary Domain:** https://inference.net
- **Machine Discovery:** Full `/llms-full.txt`, `/pricing.md`, `/answers.md`, `/ai/summary.json`, `/ai/faq.json`, `/ai/service.json`
- **Core Platform:** AI-Native Inference & GPU Serving Cloud
- **API & Webhooks:** Deterministic developer workflows

## Primary Documentation
- [Inference.net Overview](https://inference.net/): Primary product interface and specifications
- [Full AI Knowledge Corpus](https://inference.net/llms-full.txt): Single-file technical reference for LLMs and RAG
- [Pricing & Tiers](https://inference.net/pricing.md): Deterministic fee schedule
- [Verified Direct Answers](https://inference.net/answers.md): 40-60 word citable answer blocks


## Optional
- [JSON Summary](https://inference.net/ai/summary.json): Structured entity profile
- [FAQ JSON](https://inference.net/ai/faq.json): Machine-readable Q&A pairs

User-Agent: *
Allow: /
LLMs-Txt: https://inference.net/llms.txt
LLMs-Full-Txt: https://inference.net/llms-full.txt
AI-Summary: https://inference.net/ai/summary.json
AI-FAQ: https://inference.net/ai/faq.json
AI-Service: https://inference.net/ai/service.json

{
  "name": "Inference.net",
  "url": "https://inference.net",
  "category": "AI-Native Inference & GPU Serving Cloud",
  "summary": "Inference.net (https://inference.net) is a ai-native inference & gpu serving cloud engineered for deterministic API performance, machine-readable AI discovery, and transparent pricing.",
  "competitors": [
    "Baseten"
  ],
  "use_cases": [
    "Automated AI-Native Inference & GPU Serving Cloud for engineering teams",
    "Enterprise migration from Baseten"
  ],
  "tools": [
    {
      "name": "get_pricing_schedule",
      "description": "Fetch deterministic Markdown pricing for Inference.net",
      "endpoint": "https://inference.net/pricing.md"
    },
    {
      "name": "get_entity_summary",
      "description": "Fetch structured JSON entity attributes for Inference.net",
      "endpoint": "https://inference.net/ai/summary.json"
    }
  ],
  "last_verified": "2026-10-31"
}

# Inference.net — Machine-Readable Pricing (`pricing.md`)

> Verified as of 2026-10-31. Canonical URL: `https://inference.net/pricing.md`.

| Tier | Target Team | Pricing Structure | Key Included Capabilities |
| :--- | :--- | :--- | :--- |
| **Starter / Developer** | Individual engineers & prototypes | Self-serve free / usage tier | Core API, documentation, standard rate limits |
| **Growth / Pro** | Production engineering teams | Transparent monthly usage/team tier | Priority throughput, webhooks, team RBAC |
| **Enterprise** | Regulated & high-volume organizations | Custom annual contract | Dedicated infrastructure, enterprise SSO/RBAC, custom SLA |

{
  "mcpVersion": "2025-03-26",
  "name": "inference-net-agent-discovery",
  "title": "Inference.net \u2014 Official AI & Agent Discovery Surface",
  "url": "https://inference.net",
  "transport": "streamable-http",
  "resources": [
    {
      "uri": "https://inference.net/llms.txt",
      "mimeType": "text/plain"
    },
    {
      "uri": "https://inference.net/llms-full.txt",
      "mimeType": "text/plain"
    },
    {
      "uri": "https://inference.net/pricing.md",
      "mimeType": "text/markdown"
    },
    {
      "uri": "https://inference.net/ai/summary.json",
      "mimeType": "application/json"
    }
  ]
}

{
  "openapi": "3.1.0",
  "info": {
    "title": "Inference.net Agent Discovery API",
    "version": "1.0.0",
    "description": "Deterministic AI & agent discovery endpoints for Inference.net (inference.net)."
  },
  "servers": [
    {
      "url": "https://inference.net"
    }
  ],
  "paths": {
    "/ai/summary.json": {
      "get": {
        "operationId": "getEntitySummary",
        "summary": "Structured entity profile for Inference.net"
      }
    },
    "/pricing.md": {
      "get": {
        "operationId": "getPricingMarkdown",
        "summary": "Deterministic pricing tiers for Inference.net"
      }
    },
    "/llms-full.txt": {
      "get": {
        "operationId": "getFullCorpus",
        "summary": "Complete technical RAG corpus for Inference.net"
      }
    }
  }
}

Zero-Backend 13-Route Edge Router Preview (inference.net):

export default {
  async fetch(req) {
    const p = new URL(req.url).pathname;
    if (ASO_ROUTES[p]) return new Response(ASO_ROUTES[p].body, { headers: ASO_ROUTES[p].headers });
    if (p === "/robots.txt") return merge27AiCrawlerPolicy(await fetch(req)); // Preserves origin Disallow & Sitemap
    const res = await fetch(req); // inference.net origin untouched (<1ms streaming overhead)
    return new HTMLRewriter().on("head", injectLinkedSchemaGraphAndMeta).transform(withRfc8288Links(res));
  } // 13 routes: /llms.txt, /llms-full.txt, /.well-known/ai.txt, /pricing.md, /ai/*.json, /.well-known/mcp.json, /.well-known/openapi.json, /feed.xml
};

export default {
  async fetch(req) {
    const p = new URL(req.url).pathname;
    if (ASO_ROUTES[p]) return new Response(ASO_ROUTES[p].body, { headers: ASO_ROUTES[p].headers });
    if (p === "/robots.txt") return merge27AiCrawlerPolicy(await fetch(req)); // Preserves origin Disallow & Sitemap
    const res = await fetch(req); // inference.net origin untouched (<1ms streaming overhead)
    return new HTMLRewriter().on("head", injectLinkedSchemaGraphAndMeta).transform(withRfc8288Links(res));
  } // 13 routes: /llms.txt, /llms-full.txt, /.well-known/ai.txt, /pricing.md, /ai/*.json, /.well-known/mcp.json, /.well-known/openapi.json, /feed.xml
};

// middleware.ts (Vercel Edge / Next.js — included in 26-file bundle for inference.net)
import { NextResponse, type NextRequest } from 'next/server';
export function middleware(req: NextRequest) {
  const hit = ASO_ROUTES[req.nextUrl.pathname];
  if (hit) return new NextResponse(hit.body, { status: 200, headers: hit.headers });
  const res = NextResponse.next();
  res.headers.set('Link', '</llms.txt>; rel="service-doc", </.well-known/mcp.json>; rel="service-desc"');
  return res;
}
export const config = { matcher: ['/llms.txt', '/llms-full.txt', '/.well-known/:path*', '/pricing.md', '/ai/:path*'] };

# edge/nginx-aso.conf (Nginx / AWS CloudFront origin for inference.net)
location ~ ^/(llms\.txt|llms-full\.txt|pricing\.md|answers\.md|\.well-known/(ai\.txt|mcp\.json)|ai/.*\.json)$ {
  root /var/www/aso-static;
  add_header Access-Control-Allow-Origin "*" always;
  add_header Cache-Control "public, max-age=3600, s-maxage=86400" always;
  add_header Link '<https://inference.net/llms.txt>; rel="service-doc"' always;
}

Team — ran a 47-check Agent Search Optimization (ASO) audit on inference.net. We currently score 73/100 (20% Share-of-Model across 10 bottom-of-funnel ChatGPT/Perplexity buyer prompts vs Baseten) because while /llms.txt and /pricing.md are live, /.well-known/ai.txt, /ai/summary.json, and /.well-known/mcp.json return 404. ASO Studio already built our complete 26-file saturation PR + 1-Click Cloudflare Edge Worker (Pay $0 today, settle only after 99+/100 is live): https://asostudio.dev/proposal/inference-net-23f201

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)

6. Reserve Order & Unlock 26-File Bundle

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