Agentery pricing intelligence · Provider profile · Ninjadoc
Provider profile · independently tracked by Agentery
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Ninjadoc

↗ ninjadoc.ai official website

PDF document extraction with visual provenance and citation tracking

infrastructurePricing checked daily
Agentery value verdictPriced near the marketfrom $0.01/mo
Observed entry price$0.01/molowest observed monthly
Billing modelusage-based
Pricing observed24 Sept 2026latest priced read of the page
Website liveness30 Oct 2026alive · separate from pricing

What it does

The specific capability behind this listing, and where to get it.

Ninjadoc

PDF document extraction with visual provenance and citation tracking

PDFs, natural language questions → structured JSON answers with bounding boxes, citation URLs, page numbers, confidence scores, and cropped screenshots
MCPREST APIClaudeCursorMCPAPIautonomy: infrastructure

Pricing & plans

Observed public pricing for Ninjadoc, benchmarked against comparable providers. Plans, tiers, history and scenario below.

Pricing · observed daily
per · market position

$5 /

68.7% below the median. Basis: comparable plans in Document QA Agent, same buyer tier and billing unit, USD monthly, observed 2026-09-24.
this agent · $5
$8median $16$32
pricing observed 2026-09-24 · page rechecked daily · source evidence retained
What should this agent charge?

The current price sits below the comparable median.

pricing recommendation
$5
$8–$32
$16

$5 is positioned against a $8–$32 observed middle market.

Pricing checks returned

Why Agentery reaches that view

price_benchmark

68.7% below the median.

get_provider_profile · plan history

per observed 2026-09-24.

pricing recommendation

Percentile unavailable for this basis.

confidence

Source page rechecked daily.

Interactive provider scenario

Test a different price for this plan.

Move the proposed monthly price. Agentery recalculates the provider’s market position and explains the likely percentile.

$5 / month
$5 lowestmedian $16$48 highest
Competitive value position. At $5/month, this plan is 68.7% below the cohort median.
—
-68.7%
$8–$32

Is Ninjadoc good value?

How its price compares with genuinely comparable providers.

Priced near the market

Priced near the market for its buyer tier.

Basis: same-tier-tier plans in the niche, any billing unit (1 provider), USD monthly, pricing observed 2026-09-24. The Document Query plan ($0.01/mo) sits 0% above that median of $0.01. Thin evidence: fewer than five comparable providers, so treat the position as indicative. Other cohorts on this page (niche-wide tier peers, nearest products by capability) are labelled where they appear.

Observed commercial price$5/mo
NicheDocument QA Agent
Price benchmarkapplicable
How it compares

Compared with Document QA Agent

Positioned against the observed p25 / median / p75 of comparable providers at the same buyer tier and billing unit (the basis is stated with each verdict above). See the plans above for the percentile and its cohort size, and the full niche market for peers.

View the full niche →

Ninjadoc's local market

Nearest products by what they do — a different cohort from the buyer-tier benchmark above. Local median $17/mo (entry prices of 12 priced of 50 nearest products, any tier or billing unit) — Ninjadoc is 71% below it.

See the full market →
See the MCP response behind this page · get_provider_profile()
See the MCP response behind this pageget_provider_profile (get_agent_profile remains a callable alias)
{
  "agent_id": "ninjadoc",
  "name": "Ninjadoc",
  "url": "https://ninjadoc.ai",
  "logo": "https://agentery.com/logos/CP-9NKG66-ld256.png",
  "niche": "document-qa-agent",
  "category": "research-knowledge-work",
  "short_summary": "PDF document extraction with visual provenance and citation tracking",
  "task_performed": "PDF document extraction with visual provenance and citation tracking",
  "inputs_accepted": [
    "PDFs",
    "natural language questions"
  ],
  "outputs_produced": [
    "structured JSON answers with bounding boxes",
    "citation URLs",
    "page numbers",
    "confidence scores",
    "and cropped screenshots"
  ],
  "integrations_available": [
    "MCP",
    "REST API",
    "Claude",
    "Cursor"
  ],
  "protocols_or_interfaces": [
    "MCP",
    "API"
  ],
  "industry_fit": [
    "developer tools"
  ],
  "autonomy_level": "infrastructure",
  "human_approval_needed": "unclear",
  "pricing_model": "usage-based",
  "price": {
    "observed": true,
    "billing": "usage",
    "source_kind": "vendor",
    "currency": "USD",
    "lowest_monthly_usd": null,
    "monthly_usd": null,
    "headline": "$0.01 per page (usage-based; prepaid credit $5)",
    "commercial": {
      "rates": [
        {
          "line": "Document Query",
          "per": "per page",
          "text": "$0.01 per page"
        }
      ],
      "currency": "USD",
      "notes": [
        "prepaid credit: $5 (funding, not a subscription)"
      ],
      "lines": [
        {
          "name": "1,250 credits",
          "price": "$5",
          "kind": "credit_purchase",
          "unit": "credits",
          "billed": "one_off"
        },
        {
          "name": "6,250 credits",
          "price": "$25",
          "kind": "credit_purchase",
          "unit": "credits",
          "billed": "one_off"
        },
        {
          "name": "25,000 credits",
          "price": "$100",
          "kind": "credit_purchase",
          "unit": "credits",
          "billed": "one_off"
        },
        {
          "name": "125,000 credits",
          "price": "$500",
          "kind": "credit_purchase",
          "unit": "credits",
          "billed": "one_off"
        },
        {
          "name": "Document Query",
          "price": "$0.01 per page",
          "kind": "usage_rate",
          "unit": "page",
          "billed": "usage"
        }
      ]
    },
    "summary": "$0.01 per page (usage-based; prepaid credit $5). NinjaDoc offers non-expiring credit packs from $5 to $500 with pay-as-you-go document querying at approximately $0.01 per page and no subscriptions.",
    "confidence": "medium",
    "source_url": "https://ninjadoc.ai/",
    "checked_at": "2026-09-24T04:20:33.091Z",
    "amount": 5,
    "display": "From $5/mo",
    "plans": [
      {
        "name": "1,250 credits",
        "price": "$5",
        "usage": true,
        "period": "one-time",
        "persona": "individual",
        "highlights": [
          "625 pages of processing",
          "Credits never expire",
          "Access to queries and future APIs"
        ],
        "price_annual": null
      },
      {
        "name": "6,250 credits",
        "price": "$25",
        "usage": true,
        "period": "one-time",
        "persona": "pro",
        "highlights": [
          "3,125 pages of processing",
          "Credits never expire",
          "Access to queries and future APIs"
        ],
        "price_annual": null
      },
      {
        "name": "25,000 credits",
        "price": "$100",
        "usage": true,
        "period": "one-time",
        "persona": "team_sme",
        "highlights": [
          "12,500 pages of processing",
          "Credits never expire",
          "Access to queries and future APIs"
        ],
        "price_annual": null
      },
      {
        "name": "125,000 credits",
        "price": "$500",
        "usage": true,
        "period": "one-time",
        "persona": "enterprise",
        "highlights": [
          "62,500 pages of processing",
          "Credits never expire",
          "Access to queries and future APIs"
        ],
        "price_annual": null
      },
      {
        "name": "Document Query",
        "price": "$0.01 per page",
        "usage": true,
        "period": "usage",
        "persona": "individual",
        "highlights": [
          "Natural-language questions about documents",
          "2 credits per page"
        ],
        "price_annual": null
      }
    ],
    "source": "render+llm"
  },
  "trust_or_rating_signal": [],
  "evidence_quality": "high",
  "entity_type": "infrastructure",
  "regulated_data_suitability": "unclear",
  "evidence_urls": [
    "https://ninjadoc.ai"
  ],
  "last_checked": "2026-09-24",
  "profile_checked": "2026-06-19",
  "price_checked": "2026-09-24",
  "how_to_connect": {
    "website": "https://ninjadoc.ai",
    "docs": null,
    "mcp": null,
    "a2a": null,
    "api": null,
    "protocols": [
      "MCP"
    ],
    "install": null,
    "repository": null,
    "note": "Speaks MCP but publishes no endpoint we could verify — check the docs/website."
  },
  "deployment": {
    "model": "unknown",
    "both_offered": false,
    "hosted_endpoint": null,
    "install": null,
    "note": "No deployment evidence held — Agentery has no endpoint, install instruction or directory attribute for this listing.",
    "evidence": null
  },
  "licence": {
    "name": null,
    "note": "No named licence found in the retained page text or source attributes. A public repository alone does not establish an open-source licence.",
    "evidence": null
  },
  "evidence_checks": {
    "price": {
      "source_url": "https://ninjadoc.ai/",
      "last_observed_day": "2026-09-24",
      "age_days": 37,
      "verified_day": "2026-09-24",
      "note": "verified = the page-text gate ran for that scan day (day-before/day-of text check)"
    },
    "agent_card": {
      "status": "unknown",
      "note": "no Agent Card URL recorded for this listing"
    },
    "endpoint": {
      "status": "unknown",
      "note": "endpoint not yet checked"
    }
  },
  "product_group": null,
  "liveness": {
    "probed": true,
    "alive": true,
    "endpoint_kind": "site",
    "latency_ms": 439,
    "uptime_7d": 1,
    "checked_at": "2026-10-30T02:41:24.689Z",
    "consecutive_failures": 0,
    "status": "alive"
  },
  "price_extras": {
    "free_tier": null,
    "unit_cost": {
      "usdPerUnit": 0.01,
      "unit": "pages",
      "usdPer1k": 10,
      "raw": "$0.01 per page",
      "plan": "Document Query"
    }
  },
  "reported_success": null,
  "feedback": "If you actually use this provider, call report_outcome with the result. Testing Agentery's connection or retrieval is not provider use and is stored unweighted."
}