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Make your product instantly callable by every AI agent.

Users won't read your docs anymore — their AI agents will. DaaS turns your product documentation into a structured skill API that agents route, understand, and act on. Higher activation. Lower support load. Zero manual maintenance.

Works with
Apache-2.0 · self-hosted · any LLM provider · multi-tenant
Powered by · Default backed by Qwen · swap to Claude / GPT / any provider in one config line
DaaS Pipeline
$ daas generate -c products/my-product.json
  ✓ Phase 0: discover     · 1,847 docs in 3 dirs
  ✓ Phase 1: extract      · 1,847/1,847 (qwen-flash, parallel)
  ✓ Phase 2: organize     · 23 capability domains
  ✓ Phase 2c: intents     · 6 intent skills
  ✓ Phase 3: detail       · 41 SKILL.md files
  ✓ Phase 3b: intent      · adversarial recall 96%
  ✓ Phase 4: entry        · skills/my-product/SKILL.md

$ curl https://your.daas/api/route?q=how+do+i+deploy
[
  { "skill": "my-product-deploy-model",
    "score": 285,
    "reason": "intent + 3-token overlap" }
]
Products live
Intent skills
Detail skills
96%
Adversarial recall
~10s
Cache-hit rebuild
Knowledge Explorer

Explore the live skill tree.

Every product below was auto-generated by DaaS — crawled, organized, and validated. Click any product to browse its skill breakdown.

GET /api/products/oss
How it works

From raw docs to an agent surface in minutes.

Point DaaS at your documentation — any URL, any format. Within minutes your product is callable by every AI agent: Claude, GPT, in-house copilots. No manual tagging, no embeddings to retrain, no maintenance.

01

Crawl & Understand

Give a URL — DaaS crawls every page, understands its purpose, and extracts structured facts (endpoints, parameters, prerequisites, error codes).

parallel · checkpoint-resumable · any format
02

Map User Intents

Docs are grouped by capability, then cross-referenced to discover what users actually want — "How do I deploy?" maps to 4 valid paths with trade-offs.

auto-consolidation · multi-path discovery
03

Generate & Validate

Each skill goes through a 6-step pipeline with 6 quality validators. Decision trees, comparison tables, FAQs — all verified before shipping.

adversarial recall > 96% · critique loop
04

Ship Agent-Native

Your product is now an HTTP API any agent can route to. User asks → agent finds the right skill → action happens. Sub-millisecond routing, zero hallucination.

HTTP API · SDK · MCP-ready · multi-tenant
Architecture

A 7-phase LLM pipeline under the hood.

Every judgment call — what's a domain, what's an intent, which keywords match a query — is delegated to an LLM. Python orchestrates parallelism, 4-layer caching, and 6 deterministic validators.

0
Discover
scan dirs
1
Extract
JSON facts
2
Organize
domains
2b
Paths
alternatives
2c
Intents
user goals
3
Generate
validate
4
Ship
entry

Three consumption surfaces

Direct file load

Claude Code, Cursor, or any agent reads SKILL.md from disk

skills/{product}/SKILL.md

HTTP API + Web UI

Single or multi-tenant, with telemetry and workspace isolation

GET /api/route?q=...

pip install daas-sdk

LocalSkillRouter or RemoteSkillRouter for Python agents

router.route(query)
Validators, cost breakdown & caching details

6 Deterministic Validators

ValidatorCatches
decision_tree_falsifiabilitySubjective conditions
faq_counter_examplesMissing wrong-path entries
faq_dedup_with_decision_treeFAQs that rephrase the tree
keyword_coverageMissing technical terms
reverse_validationContradicted linked skills
path_label_honestyUndocumented path verbs

Cost & Latency (2,000 docs)

PhaseColdCachedCost
Extract~25 min~5 s$2.00
Organize~3 min<1 s$0.50
Paths + Intents~2 min<1 s$0.40
Generate~3 min<1 s$2.00
Intent skills~5 min<1 s$5.00
Total~37 min~10 s~$10
4-layer smart cache
CompressionSHA256(chunk) ExtractionSHA256(content+prompt) OrganizationSHA256(manifest) PathsSHA256(summary)
One-click distribute

Ship every workspace as a Claude Code plugin.

Hit Publish in your dashboard. DaaS pushes the workspace to a GitHub repo formatted exactly like Anthropic's official anthropics/skills marketplace. Users install your skills with one slash command.

1
Click Publish in DaaS
Per workspace · creates the repo on first push
2
DaaS commits to GitHub
daas-skills-{workspace} · marketplace.json + README + skills/
3
User installs in Claude Code
One command. Skills load on demand.
Claude Code
> /plugin marketplace add chenkai66/daas-skills-vercel
  ✓ Marketplace 'daas-skills-vercel' added

> /plugin install vercel@daas-skills-vercel
  ✓ Installed plugin 'vercel' · 28 skills loaded

> How do I deploy a Next.js app to Vercel?
  → routing to vercel-deploy-application (intent)
  → loading vercel-deployment (guide)
  Step 1: Connect your Git provider in Vercel Dashboard...
Anthropic-spec compliant Same .claude-plugin/marketplace.json format the official skills repo uses.
Auto-discovered Aggregator sites (claudemarketplaces.com, lobehub) crawl GitHub — your repo shows up automatically.
Versioned + reproducible Each publish is a UTC-timestamped commit. Re-publish on doc updates without breaking installs.
Knowledge Graph

See how your products connect.

Every product, intent, and cross-product combo mapped as a live force-directed graph. Edges represent real co-occurrence in routing telemetry — not hand-drawn diagrams.

Products
Cross-product edges
Discovered combos
Generative Engine Optimization

Get cited inside the answer, not just ranked.

Classic SEO ranks you on Google. GEO gets your product recommended by ChatGPT, Perplexity, Claude and Gemini. DaaS already structures your docs into skills — GEO exposes them on every surface a generative engine crawls, parses, and quotes, then measures whether you actually surface.

Platform GEO score
Products optimized
Citable AI surfaces
Welcomed crawlers GPTBot ClaudeBot PerplexityBot Google-Extended Gemini
01

Generate test queries

Brand-free questions are synthesised straight from each intent — so we measure organic surfacing, never a brand lookup.

from the skill graph · zero hand-written prompts
02

Measure & diagnose

Each query runs through our own router. A miss is split into coverage gap vs surfacing gap vs wrong product — the exact thing to fix.

/api/route is the target AND the ruler
03

Guarded rewrite

GEO-paper levers (answer-first, statistics, citations) are applied to the weakest skills — guarded by a key-point-recall check so accuracy is never traded for visibility.

no facts, endpoints or numbers dropped
Live workspace

Already powering products live.

From Alibaba Cloud infrastructure to international SaaS platforms — each chip is a real product whose docs DaaS has ingested, organized, and made query-ready.

Pricing

A marketplace for product intelligence.

Product companies publish their docs as AI-callable skills. Agent developers query them all through a single API.

Team
¥999 / mo · $149
1 workspace · 5 products · 100k routes/mo
  • Hosted skill generation from your docs
  • Weekly auto-rebuild on doc change
  • Distribution to all MCP clients
  • Email support · best-effort SLA
Scale
Business
¥4,999 / mo · $699
5 workspaces · unlimited products · 1M routes/mo
  • Everything in Team
  • Daily auto-rebuild · 99.5% SLA
  • Slack/Lark support · 24h response
  • Telemetry dashboard + Gap Radar
Contact Sales
Community
Free · Apache-2.0
Self-host single-tenant · no limits
  • Full pipeline source on GitHub
  • Python SDK + per-product MCP servers
  • All 6 deterministic validators
  • Multi-LLM (DashScope / OpenAI / Anthropic / vLLM)
Get Started
Hosted
Team
¥999 / mo · $149
100k routes/mo · zero ops · 14-day trial
  • Hosted multi-tenant routing
  • Weekly auto-rebuild on doc change
  • Telemetry + Doc Gap Radar (LLM-clustered)
  • Overage: ¥5 / 1k routes (or $0.75)
🧪 Demo mode is on — judges can test the full Subscribe → QR → auto-pay → API key flow without spending money.