~ · home · developer-tools-infra ai-data-engineering · 22

AI Data Engineering

Query this niche via MCPmarket_report({ query: "AI Data Engineering", response_mode: "summary" })
active marketmarket pulse 41/100commercial money present0 new builders in 30d22 listings
basis: all observed monthly plans · commercial-form-v2
Agents · median
None priced — too few for a Agents median.
MCP servers · median
None priced — too few for a MCP servers median.

All plans — Agents vs MCPs

each dot = one provider · log scale
No providers priced at the All tier yet.

All plans

0 priced
Providervs its cohort medianMonthly
Position is relative to the provider's own delivery-type median at this tier — never a blended one.
What the figures on this page are. This page is Agentery's fixed-niche view of AI Data Engineering (latest observation 2026-10-14T03:32:48.116Z). The headline medians above are computed from that data per delivery type and buyer-tier tab: on a tier tab, the median of each provider's plan at that tier; on “All”, every priced plan point across tiers pooled. Small cohorts show as “too few” rather than a median. The embedded response below is the broader fixed-niche report: its by_provider_type.*.median pools all tiers, pricing.byPersona.* is per buyer tier, and the unit cohorts (e.g. Pro flat) are per tier and billing unit — so those blocks legitimately differ from one headline figure. Over MCP today the advertised tools are market_report (a semantic neighbourhood for your query, not this fixed niche) and price_benchmark (query/task); niche_report stays callable as a legacy alias. Their cohorts are defined differently, so their numbers can differ from this page.
market_reportprice_benchmark
See the MCP response behind this pagefixed-niche report (legacy niche_report alias, full mode) — broader than the headline figure
{
  "niche": "ai-data-engineering",
  "parent_sector": "developer-tools-infra",
  "provider_type_pricing": {
    "slug": "ai-data-engineering",
    "pricing_basis": "lowest_observed_monthly_usd",
    "provider_type_methodology": "commercial-form-v2",
    "provider_type_methodology_published_at": "2026-07-31",
    "blended": {
      "median": null,
      "p25": null,
      "p75": null,
      "providers": 0
    },
    "by_provider_type": {
      "agent": {
        "median": null,
        "p25": null,
        "p75": null,
        "providers": 0,
        "publishable": false,
        "confidence": "insufficient",
        "reason": "Fewer than three comparable priced Agent-economy products are available."
      },
      "mcp": {
        "median": null,
        "p25": null,
        "p75": null,
        "providers": 0,
        "publishable": false,
        "confidence": "insufficient",
        "reason": "Fewer than three comparable priced MCP servers are available."
      }
    },
    "recommended_cohort": null,
    "recommendation_reason": "Choose the cohort according to the commercial delivery type being assessed.",
    "fallback_context": null,
    "context_note": null
  },
  "crowding_level": "crowded",
  "observed_node_count": 18,
  "adjacent_niches": [
    "ai-frontend-coding",
    "incident-response-sre",
    "mcp-platform-provider",
    "legacy-code-modernization",
    "infrastructure-provisioning-iac",
    "on-call-management-agent"
  ],
  "market_pulse": {
    "pulse": 41,
    "drivers": [
      "enterprise money present"
    ],
    "price_move_30d_pct": null,
    "money_share": 0.25,
    "entry_rate": 0,
    "alive_share": 1
  },
  "price_move": {
    "d_pct": 0,
    "w_pct": 0,
    "m_pct": 0,
    "comparable_agents": 0,
    "quarantined_agents": 0,
    "confidence": "gap",
    "published": {
      "d": false,
      "w": false,
      "m": false
    },
    "held_reason": {
      "d": null,
      "w": null,
      "m": null
    },
    "driver": {
      "d": null,
      "w": null,
      "m": null
    },
    "tier_contribution": {
      "d": {
        "individual": 0,
        "pro": 0,
        "team_sme": 0,
        "enterprise": 0
      },
      "w": {
        "individual": 0,
        "pro": 0,
        "team_sme": 0,
        "enterprise": 0
      },
      "m": {
        "individual": 0,
        "pro": 0,
        "team_sme": 0,
        "enterprise": 0
      }
    },
    "tier_series": {
      "individual": [
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100
      ],
      "pro": [
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100
      ],
      "team_sme": [
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100
      ],
      "enterprise": [
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100,
        100
      ]
    },
    "tier_own_move": {
      "d": {
        "individual": 0,
        "pro": 0,
        "team_sme": 0,
        "enterprise": 0
      },
      "w": {
        "individual": 0,
        "pro": 0,
        "team_sme": 0,
        "enterprise": 0
      },
      "m": {
        "individual": 0,
        "pro": 0,
        "team_sme": 0,
        "enterprise": 0
      }
    },
    "tier_agents": {
      "individual": 3,
      "pro": 0,
      "team_sme": 0,
      "enterprise": 0
    },
    "obs_range": {
      "d": null,
      "w": null,
      "m": null
    },
    "tier_obs_range": {
      "d": {
        "individual": null,
        "pro": null,
        "team_sme": null,
        "enterprise": null
      },
      "w": {
        "individual": null,
        "pro": null,
        "team_sme": null,
        "enterprise": null
      },
      "m": {
        "individual": null,
        "pro": null,
        "team_sme": null,
        "enterprise": null
      }
    }
  },
  "pricing": {
    "sampleSize": 22,
    "observed": 4,
    "byPersona": {
      "free": {
        "n": 2,
        "nPriced": 0,
        "reliability": "none",
        "median": null,
        "p25": null,
        "p75": null,
        "min": null,
        "max": null,
        "mean": null,
        "stdev": null,
        "usageShare": 0
      },
      "individual": {
        "n": 2,
        "nPriced": 2,
        "reliability": "low",
        "median": 0.57,
        "p25": 0.43,
        "p75": 0.72,
        "min": 0.29,
        "max": 0.86,
        "mean": 0.57,
        "stdev": 0.4,
        "usageShare": 1
      },
      "pro": {
        "n": 1,
        "nPriced": 1,
        "reliability": "none",
        "median": 2,
        "p25": 2,
        "p75": 2,
        "min": 2,
        "max": 2,
        "mean": 2,
        "stdev": 0,
        "usageShare": 1
      },
      "team_sme": {
        "n": 1,
        "nPriced": 1,
        "reliability": "none",
        "median": 4,
        "p25": 4,
        "p75": 4,
        "min": 4,
        "max": 4,
        "mean": 4,
        "stdev": 0,
        "usageShare": 1
      },
      "enterprise": {
        "n": 1,
        "nPriced": 1,
        "reliability": "none",
        "median": 3,
        "p25": 3,
        "p75": 3,
        "min": 3,
        "max": 3,
        "mean": 3,
        "stdev": 0,
        "usageShare": 1
      }
    },
    "byPersonaMonthly": {
      "free": {
        "nMonthly": 0,
        "p25": null,
        "median": null,
        "p75": null,
        "confidence": "none",
        "usageShare": 0,
        "mixedBilling": false,
        "monthlyComparable": false
      },
      "individual": {
        "nMonthly": 0,
        "p25": null,
        "median": null,
        "p75": null,
        "confidence": "none",
        "usageShare": 1,
        "mixedBilling": false,
        "monthlyComparable": false
      },
      "pro": {
        "nMonthly": 0,
        "p25": null,
        "median": null,
        "p75": null,
        "confidence": "none",
        "usageShare": 1,
        "mixedBilling": false,
        "monthlyComparable": false
      },
      "team_sme": {
        "nMonthly": 0,
        "p25": null,
        "median": null,
        "p75": null,
        "confidence": "none",
        "usageShare": 1,
        "mixedBilling": false,
        "monthlyComparable": false
      },
      "enterprise": {
        "nMonthly": 0,
        "p25": null,
        "median": null,
        "p75": null,
        "confidence": "none",
        "usageShare": 1,
        "mixedBilling": false,
        "monthlyComparable": false
      }
    },
    "byTierCohorts": {
      "status": "insufficient",
      "cohorts": [],
      "rejected": {
        "usage_not_monthly": 5
      },
      "evidence": {
        "status": "observed_offers_only",
        "single_observations": [],
        "observed_offers": [
          {
            "billing": "usage",
            "unit": "flat",
            "count": 2,
            "offers": [
              {
                "provider": "docetl",
                "tier": "individual",
                "billing": "usage",
                "unit": "flat",
                "price": "$0.29",
                "monthly_usd": null
              },
              {
                "provider": "docetl",
                "tier": "individual",
                "billing": "usage",
                "unit": "flat",
                "price": "$0.86",
                "monthly_usd": null
              }
            ]
          },
          {
            "billing": "usage",
            "unit": "other_usage",
            "count": 3,
            "offers": [
              {
                "provider": "cortex_code",
                "tier": "pro",
                "billing": "usage",
                "unit": "other_usage",
                "price": "$2.00 / per credit ($USD)",
                "monthly_usd": null
              },
              {
                "provider": "cortex_code",
                "tier": "enterprise",
                "billing": "usage",
                "unit": "other_usage",
                "price": "$3.00 / per credit ($USD)",
                "monthly_usd": null
              },
              {
                "provider": "cortex_code",
                "tier": "team_sme",
                "billing": "usage",
                "unit": "other_usage",
                "price": "$4.00 / per credit ($USD)",
                "monthly_usd": null
              }
            ]
          }
        ],
        "coverage": {
          "priced_providers": 2,
          "normalized_observations": 0,
          "comparable_providers": 0,
          "strict_cohorts": 0,
          "exclusion_reasons": {
            "usage_not_monthly": 5
          }
        }
      }
    },
    "quoteOnlyProvidersByTier": {
      "pro": 0,
      "enterprise": 0,
      "team_sme": 0,
      "individual": 0
    },
    "billingMix": {
      "usage": 2,
      "free": 2
    },
    "freeTierShare": 0.5,
    "medianLowestUsd": null
  },
  "movement": null,
  "index_series": {
    "series": [
      {
        "day": "2026-09-15",
        "index": 100,
        "pairs": 3,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-16",
        "index": 100,
        "pairs": 3,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-17",
        "index": 100,
        "pairs": 3,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-18",
        "index": 100,
        "pairs": 3,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-19",
        "index": 100,
        "pairs": 3,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-20",
        "index": 100,
        "pairs": 3,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-21",
        "index": 100,
        "pairs": 3,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-22",
        "index": 100,
        "pairs": 3,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-23",
        "index": 100,
        "pairs": 3,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-24",
        "index": 100,
        "pairs": 3,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-25",
        "index": 100,
        "pairs": 3,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-26",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-27",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-28",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-29",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-09-30",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-01",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-02",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-03",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-04",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-05",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-06",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-07",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-08",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-09",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-10",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-11",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-12",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-13",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      },
      {
        "day": "2026-10-14",
        "index": 100,
        "pairs": 0,
        "dayChangePct": 0
      }
    ],
    "latest": 100,
    "day_change_pct": 0,
    "methodology": "Chained daily price index, base 100 on the first priced scan day (29 Jun 2026). The overall index is the COMPOSITE of the four buyer-tier indices (individual / pro / team&sme / enterprise): each day it moves by the equal-weighted average of the tiers' moves. Each tier index is like-for-like — only agents priced on both consecutive scan days (per-agent ratios, geometric mean, clipped to [0.2, 5]) — so composition changes (agents revealing or hiding prices) can never move it."
  },
  "top_agents": [
    {
      "agent_id": "cortex_code",
      "name": "Cortex Code",
      "url": "https://www.snowflake.com/en/product/features/cortex-code/",
      "short_summary": "Data-native AI coding agent that builds data pipelines, analytics, ML models, apps and AI agents from natural language conversations grounded in enterprise dat…",
      "price": {
        "commercial": {
          "rates": [
            {
              "line": "Standard",
              "per": "per credit",
              "text": "$2 per credit"
            },
            {
              "line": "Enterprise",
              "per": "per credit",
              "text": "$3 per credit"
            },
            {
              "line": "Business Critical",
              "per": "per credit",
              "text": "$4 per credit"
            }
          ],
          "currency": "USD",
          "lines": [
            {
              "name": "Standard",
              "price": "$2.00 / per credit ($USD)",
              "kind": "usage_rate",
              "unit": "credit",
              "billed": "usage"
            },
            {
              "name": "Enterprise",
              "price": "$3.00 / per credit ($USD)",
              "kind": "usage_rate",
              "unit": "credit",
              "billed": "usage"
            },
            {
              "name": "Business Critical",
              "price": "$4.00 / per credit ($USD)",
              "kind": "usage_rate",
              "unit": "credit",
              "billed": "usage"
            }
          ]
        },
        "observed": true,
        "billing": "usage",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "$2 per credit; $3 per credit (usage-based)",
        "summary": "$2 per credit; $3 per credit (usage-based). Snowflake offers consumption-based pricing starting at $2.00 per credit for the Standard edition, with Enterprise at $3.00 and Business Critical at $4.00 per credit."
      },
      "evidence_quality": "high",
      "upvotes": 0
    },
    {
      "agent_id": "entity_resolution",
      "name": "Senzing",
      "url": "https://mcp.senzing.com",
      "short_summary": "provides entity resolution knowledge to AI assistants via MCP, including data mapping, SDK code generation, documentation search, error troubleshooting, and ER…",
      "price": {
        "observed": false,
        "billing": "not_found",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "No public subscription or usage pricing was observed; the homepage mentions a free evaluation license but provides no plan prices."
      },
      "evidence_quality": "high",
      "upvotes": 0
    },
    {
      "agent_id": "genesis_computing",
      "name": "Enterprise-ready AI Data Agents",
      "url": "https://genesiscomputing.ai/",
      "short_summary": "autonomously executes complete data engineering workflows including data ingestion, source-to-target mapping, writing pipeline code, documentation, testing, gi…",
      "price": {
        "observed": false,
        "billing": "not_found",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "No public pricing was observed on the supplied homepage."
      },
      "evidence_quality": "high",
      "upvotes": 0
    },
    {
      "agent_id": "google_cloud_agent",
      "name": "Google Cloud Agent",
      "url": "https://docs.cloud.google.com/architecture/agentic-ai-data-science",
      "short_summary": "automates data science workflows, running complex data analytics and machine learning tasks via a multi-agent system using natural language commands",
      "price": {
        "observed": false,
        "billing": "not_found",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "No public pricing or subscription plans were observed in the supplied pages."
      },
      "evidence_quality": "high",
      "upvotes": 0
    },
    {
      "agent_id": "ascend_io",
      "name": "Agentic data engineering",
      "url": "https://ascend.io/agentic-data-engineering",
      "short_summary": "automates, optimizes and maintains data engineering pipelines using AI agents (building, monitoring, debugging, fixing issues, writing commit messages, preppin…",
      "price": {
        "observed": false,
        "billing": "not_found",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "No public price found on the vendor site."
      },
      "evidence_quality": "medium",
      "upvotes": 0
    },
    {
      "agent_id": "armor",
      "name": "Armor",
      "url": "https://smithery.ai/server/anomalyarmor-uib0/armor",
      "short_summary": "Data observability for AI agents. Query alerts, monitor freshness, investigate schema drift, and trace lineage across your data warehouse via 53 MCP tools.",
      "price": {
        "observed": false,
        "billing": "not_found",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "No public pricing is shown for AnomalyArmor on the supplied homepage."
      },
      "evidence_quality": "low",
      "upvotes": 0
    },
    {
      "agent_id": "data_transform",
      "name": "Data Converter",
      "url": "https://smithery.ai/server/data-transform-agent/data-transform",
      "short_summary": "Convert data between over 40 formats including JSON, CSV, Excel, and PDF. Restructure complex schemas into custom layouts to ensure seamless data integration.…",
      "price": {
        "observed": false,
        "billing": "not_found",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "No public pricing was observed on the available homepage."
      },
      "evidence_quality": "low",
      "upvotes": 0
    },
    {
      "agent_id": "datagendev",
      "name": "DataGen",
      "url": "https://smithery.ai/server/kuoyusheng/datagendev",
      "short_summary": "Run and orchestrate DataGen deployments from validation through execution and monitoring. Generate copy-ready curl commands, input/output schemas, and accessib…",
      "price": {
        "observed": false,
        "billing": "not_found",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "No public pricing is shown for DataGen on the supplied page."
      },
      "evidence_quality": "low",
      "upvotes": 0
    },
    {
      "agent_id": "data_pipeline_skill",
      "name": "Data Pipeline Skill",
      "url": "https://agentconn.com/skills/data-pipeline/",
      "short_summary": "AI-powered ETL pipeline skill for Semantic Kernel that transforms, cleans, and loads data using natural language descriptions instead of scripts. Handles schem…",
      "price": {
        "commercial": {
          "currency": "USD",
          "lines": [
            {
              "name": "Data Pipeline",
              "price": "0USD",
              "kind": "free",
              "billed": "monthly"
            }
          ]
        },
        "observed": true,
        "billing": "free",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "Free",
        "summary": "Free. The Data Pipeline skill is listed with a structured offer of 0USD and is described as open source."
      },
      "evidence_quality": "unclear",
      "upvotes": 0
    },
    {
      "agent_id": "dataspoke_baseline",
      "name": "Dataspoke Baseline",
      "url": "https://github.com/selhorys/dataspoke-baseline",
      "short_summary": "AI-powered sidecar extension for DataHub that adds ingestion control, validation, ontology generation, metadata generation, and governance. Includes an AI scaf…",
      "price": {
        "observed": false,
        "billing": "not_found",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "No public pricing amounts or plan details were observed on the supplied homepage, and no pricing page was available."
      },
      "evidence_quality": "unclear",
      "upvotes": 0
    }
  ],
  "platforms_also_here": [
    {
      "agent_id": "docsdatabrickscom",
      "name": "Docsdatabrickscom",
      "url": "https://docs.databricks.com/aws/en/generative-ai/agent-framework/agent-tool",
      "short_summary": "documentation for connecting AI agent tools and data, including searching documents, querying databases, calling REST APIs, and running custom code via MCP ser…",
      "price": {
        "observed": false,
        "billing": "not_found",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "No public price found on the vendor site."
      },
      "home_niche": "developer-portal-api-docs",
      "also_covers": true,
      "upvotes": 0
    }
  ],
  "page_url": "https://agentery.com/market/ai-data-engineering",
  "summary": {
    "niche": "ai-data-engineering",
    "sector": "developer-tools-infra",
    "pricing_by_provider_type": {
      "headline": "No published benchmark for ai-data-engineering yet — too few comparable priced providers.",
      "benchmarks": [],
      "warnings": [
        "No priced providers meet the benchmark bar for this scope."
      ],
      "full_pricing_via": {
        "tool": "price_benchmark",
        "arguments": {
          "niche": "ai-data-engineering"
        },
        "note": "add provider_type + buyer_tier for a specific cohort"
      }
    },
    "page_url": "https://agentery.com/market/ai-data-engineering",
    "counts": {
      "listings_with_price_capture": 22,
      "listings_with_observed_public_price": 4,
      "providers_with_numeric_monthly_price_latest_scan": null,
      "like_for_like_comparable_pairs": null
    },
    "movement": {
      "d": {
        "published": false,
        "value_pct": null,
        "held_reason": null
      },
      "w": {
        "published": false,
        "value_pct": null,
        "held_reason": null
      },
      "m": {
        "published": false,
        "value_pct": null,
        "held_reason": null
      }
    },
    "pricing_version": "cohorts-1",
    "pricing_status": "observed_offers_only",
    "pricing_by_tier": null,
    "observed_offers": [
      {
        "billing": "usage",
        "unit": "flat",
        "count": 2,
        "offers": [
          {
            "provider": "docetl",
            "tier": "individual",
            "billing": "usage",
            "unit": "flat",
            "price": "$0.29",
            "monthly_usd": null
          },
          {
            "provider": "docetl",
            "tier": "individual",
            "billing": "usage",
            "unit": "flat",
            "price": "$0.86",
            "monthly_usd": null
          }
        ]
      },
      {
        "billing": "usage",
        "unit": "other_usage",
        "count": 3,
        "offers": [
          {
            "provider": "cortex_code",
            "tier": "pro",
            "billing": "usage",
            "unit": "other_usage",
            "price": "$2.00 / per credit ($USD)",
            "monthly_usd": null
          },
          {
            "provider": "cortex_code",
            "tier": "enterprise",
            "billing": "usage",
            "unit": "other_usage",
            "price": "$3.00 / per credit ($USD)",
            "monthly_usd": null
          },
          {
            "provider": "cortex_code",
            "tier": "team_sme",
            "billing": "usage",
            "unit": "other_usage",
            "price": "$4.00 / per credit ($USD)",
            "monthly_usd": null
          }
        ]
      }
    ],
    "pricing_coverage": {
      "listings_with_price_capture": 22,
      "listings_with_observed_public_price": 4,
      "normalized_observations": 0,
      "comparable_providers": 0,
      "strict_cohorts": 0,
      "exclusion_reasons": {
        "usage_not_monthly": 5
      }
    },
    "pricing_note": "No comparable cohort formed (a benchmark needs >=2 providers sharing a buyer tier AND billing unit). observed_offers lists the REAL provider offers, grouped and labelled by billing type — each is a single observed price, never aggregated across mixed units, periods or tiers.",
    "pricing_excluded_observations": {
      "usage_not_monthly": 5
    },
    "billing_mix": {
      "usage": 2,
      "free": 2
    },
    "free_tier_share": 0.5,
    "top_providers": [
      {
        "agent_id": "cortex_code",
        "name": "Cortex Code",
        "price": {
          "commercial": {
            "rates": [
              {
                "line": "Standard",
                "per": "per credit",
                "text": "$2 per credit"
              },
              {
                "line": "Enterprise",
                "per": "per credit",
                "text": "$3 per credit"
              },
              {
                "line": "Business Critical",
                "per": "per credit",
                "text": "$4 per credit"
              }
            ],
            "currency": "USD",
            "lines": [
              {
                "name": "Standard",
                "price": "$2.00 / per credit ($USD)",
                "kind": "usage_rate",
                "unit": "credit",
                "billed": "usage"
              },
              {
                "name": "Enterprise",
                "price": "$3.00 / per credit ($USD)",
                "kind": "usage_rate",
                "unit": "credit",
                "billed": "usage"
              },
              {
                "name": "Business Critical",
                "price": "$4.00 / per credit ($USD)",
                "kind": "usage_rate",
                "unit": "credit",
                "billed": "usage"
              }
            ]
          },
          "observed": true,
          "billing": "usage",
          "lowest_monthly_usd": null,
          "monthly_usd": null,
          "headline": "$2 per credit; $3 per credit (usage-based)",
          "summary": "$2 per credit; $3 per credit (usage-based). Snowflake offers consumption-based pricing starting at $2.00 per credit for the Standard edition, with Enterprise at $3.00 and Business Critical at $4.00 per credit."
        },
        "observed": true
      },
      {
        "agent_id": "entity_resolution",
        "name": "Senzing",
        "price": {
          "observed": false,
          "billing": "not_found",
          "lowest_monthly_usd": null,
          "monthly_usd": null,
          "headline": "No public price found",
          "summary": "No public subscription or usage pricing was observed; the homepage mentions a free evaluation license but provides no plan prices."
        },
        "observed": false
      },
      {
        "agent_id": "genesis_computing",
        "name": "Enterprise-ready AI Data Agents",
        "price": {
          "observed": false,
          "billing": "not_found",
          "lowest_monthly_usd": null,
          "monthly_usd": null,
          "headline": "No public price found",
          "summary": "No public pricing was observed on the supplied homepage."
        },
        "observed": false
      },
      {
        "agent_id": "google_cloud_agent",
        "name": "Google Cloud Agent",
        "price": {
          "observed": false,
          "billing": "not_found",
          "lowest_monthly_usd": null,
          "monthly_usd": null,
          "headline": "No public price found",
          "summary": "No public pricing or subscription plans were observed in the supplied pages."
        },
        "observed": false
      },
      {
        "agent_id": "ascend_io",
        "name": "Agentic data engineering",
        "price": {
          "observed": false,
          "billing": "not_found",
          "lowest_monthly_usd": null,
          "monthly_usd": null,
          "headline": "No public price found",
          "summary": "No public price found on the vendor site."
        },
        "observed": false
      }
    ],
    "suggested_next_calls": [
      {
        "tool": "price_benchmark",
        "arguments": {
          "niche": "ai-data-engineering"
        },
        "purpose": "full observed price distribution + per-tier medians for this niche"
      },
      {
        "tool": "niche_report",
        "arguments": {
          "niche": "ai-data-engineering",
          "response_mode": "full"
        },
        "purpose": "the complete report incl. index series and tier decomposition"
      },
      {
        "tool": "suggest_alternatives",
        "arguments": {
          "agent_id": "cortex_code"
        },
        "purpose": "comparable (optionally cheaper) providers to a named agent"
      },
      {
        "tool": "get_agent_profile",
        "arguments": {
          "agent_id": "cortex_code"
        },
        "purpose": "full profile, integrations and pricing for one provider"
      }
    ]
  }
}
Full market

2 providers, one sortable view

Dense enough for many listings; progressive disclosure keeps mobile usable.

Showing only providers with a published price or a free plan. $29 = lowest observed monthly · Free = free to use · Free tier = free plan + paid options.