Agentery pricing intelligence · Provider profile · Ai Rete Rag
Provider profile · independently tracked by Agentery
AR

Ai Rete Rag

ai-rete-rag.com official website

ai·rete·rag splits deciding from explaining. The verdict comes from a Rete production-rule engine — deterministic, reproducible, and traceable to the exact rul…

infrastructurePricing checked daily
Agentery price verdictInsufficient peerscannot benchmark yet
Observed entry price$1/molowest observed monthly
Billing modelunclear
Last checkedpricing & liveness

What it does

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

ai·rete·rag splits deciding from explaining. The verdict comes from a Rete production-rule engine — deterministic, reproducible, and traceable to the exact rule that fired, with salience deciding which rule wins when two disagree. Only then does an LLM run, grounded by retrieval over your own policy documents, to render that verdict into prose that cites real policy text. The model never decides anything, so an explanation can't invent a threshold your rulebook doesn't have. Eight tools cover the whole loop: hand it a written policy and get back draft rules that cite the sentence each one encodes, review them, save them as YAML, ingest supporting documents, then decide against them — and ask why any rule didn't fire. Eight demo domains (loan, fraud, clinical, insurance, legal, blockchain, operations, e-commerce) work without a key.

MCPMCPautonomy: infrastructure

Official Ai Rete Rag links

Pricing & plans

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

Pricing · observed daily
Supporter · market position

$1 /mo

Observed plan · market position not comparable on a monthly basis.
this agent · $1
$8median $89
observed 2026-08-08 · rechecked daily · source evidence retained
What should this agent charge?

This plan sits close to the market.

pricing recommendation
$1
$8$89

No monthly-comparable cohort to benchmark this plan against yet.

Pricing checks returned

Why Agentery reaches that view

price_benchmark

Not monthly-comparable.

get_agent_profile · plan history

Supporter observed 2026-08-08.

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.

$1 / month
$1 lowestmedian $89 highest
Not comparable This plan's basis isn't monthly-comparable.
$8$89

Is Ai Rete Rag good value?

How its price compares with genuinely comparable providers.

Not enough peers

Not enough evidence yet to call it good — or poor — value.

Too few comparable providers at the same buyer tier and billing unit to benchmark this price honestly.

Observed commercial price$1/mo
Niche
Price benchmarknot applicable
What to compare instead

Check capability before deciding

Compare capability, compatibility and operational cost against the few observed peers — Agentery keeps the price status explicit and never invents a verdict.

See the MCP response behind this page · get_agent_profile()
See the MCP response behind this pageget_agent_profile
{
  "agent_id": "ai_rete_rag",
  "name": "Ai Rete Rag",
  "url": "https://ai-rete-rag.com/",
  "logo": null,
  "niche": null,
  "category": null,
  "short_summary": "ai·rete·rag splits deciding from explaining. The verdict comes from a Rete production-rule engine — deterministic, reproducible, and traceable to the exact rul…",
  "task_performed": "ai·rete·rag splits deciding from explaining. The verdict comes from a Rete production-rule engine — deterministic, reproducible, and traceable to the exact rule that fired, with salience deciding which rule wins when two disagree. Only then does an LLM run, grounded by retrieval over your own policy documents, to render that verdict into prose that cites real policy text. The model never decides anything, so an explanation can't invent a threshold your rulebook doesn't have.\n\nEight tools cover the whole loop: hand it a written policy and get back draft rules that cite the sentence each one encodes, review them, save them as YAML, ingest supporting documents, then decide against them — and ask why any rule didn't fire. Eight demo domains (loan, fraud, clinical, insurance, legal, blockchain, operations, e-commerce) work without a key.",
  "inputs_accepted": [],
  "outputs_produced": [],
  "integrations_available": [
    "MCP"
  ],
  "protocols_or_interfaces": [
    "MCP"
  ],
  "industry_fit": [
    "developer tools"
  ],
  "autonomy_level": "infrastructure",
  "human_approval_needed": "unclear",
  "pricing_model": "unclear",
  "price": {
    "observed": true,
    "billing": "freemium",
    "currency": "USD",
    "lowest_monthly_usd": 1,
    "monthly_usd": 1,
    "headline": "Free tier, then from $1/mo",
    "summary": "Free tier, then from $1/mo. ai·rete·rag offers a permanent free plan, paid monthly plans from $1/month to $39/month, a $119/month Pro plan billed annually, and custom Enterprise pricing.",
    "confidence": "high",
    "source_url": "https://ai-rete-rag.com/pricing",
    "checked_at": "2026-08-08T04:40:13.665Z",
    "amount": 1,
    "display": "From $1/mo",
    "plans": [
      {
        "name": "Free",
        "price": "$0",
        "period": "month",
        "persona": "free",
        "highlights": [
          "Free forever",
          "1 domain",
          "1,000 decisions/month",
          "10 MB document storage",
          "Public API access"
        ],
        "price_annual": null
      },
      {
        "name": "Supporter",
        "price": "$1 / month",
        "period": "month",
        "persona": "individual",
        "highlights": [
          "3 domains",
          "10,000 decisions/month",
          "50 MB document storage",
          "Team members",
          "Community support"
        ],
        "price_annual": null
      },
      {
        "name": "Builder",
        "price": "$19 / month",
        "period": "month",
        "persona": "individual",
        "highlights": [
          "5 domains",
          "25,000 decisions/month",
          "250 MB document storage",
          "Team members",
          "Email support"
        ],
        "price_annual": null
      },
      {
        "name": "Standard",
        "price": "$39 / month",
        "period": "month",
        "persona": "pro",
        "highlights": [
          "10 domains",
          "100,000 decisions/month",
          "1 GB document storage",
          "Team members",
          "Email support"
        ],
        "price_annual": null
      },
      {
        "name": "Pro",
        "price": "$119 / month",
        "period": "month",
        "persona": "pro",
        "highlights": [
          "Billed annually",
          "Save $360/yr",
          "Unlimited domains",
          "500,000 decisions/month",
          "10 GB document storage",
          "Priority support"
        ],
        "price_annual": null
      },
      {
        "name": "Enterprise",
        "price": "Custom",
        "period": null,
        "persona": "enterprise",
        "highlights": [
          "Unlimited everything",
          "Self-hosted deployment option",
          "Custom LLM endpoints",
          "Dedicated success engineer",
          "Custom SLA"
        ],
        "price_annual": null
      }
    ],
    "source": "render+llm"
  },
  "trust_or_rating_signal": [],
  "evidence_quality": "medium",
  "entity_type": "infrastructure",
  "regulated_data_suitability": "unclear",
  "evidence_urls": [
    "https://ai-rete-rag.com/"
  ],
  "last_checked": "2026-08-08",
  "how_to_connect": {
    "website": "https://ai-rete-rag.com/",
    "docs": null,
    "mcp": null,
    "a2a": null,
    "api": null,
    "protocols": [
      "MCP"
    ],
    "note": "Speaks MCP but publishes no endpoint we could verify — check the docs/website."
  },
  "liveness": {
    "probed": false,
    "alive": null,
    "endpoint_kind": null,
    "latency_ms": null,
    "uptime_7d": null,
    "checked_at": null,
    "consecutive_failures": 0,
    "status": "unknown"
  },
  "price_extras": {
    "free_tier": null,
    "unit_cost": null
  },
  "reported_success": null,
  "feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}