Deep Research Agent

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        "dayChangePct": 0
      },
      {
        "day": "2026-07-20",
        "index": 100,
        "pairs": 11,
        "dayChangePct": 0
      },
      {
        "day": "2026-07-21",
        "index": 100,
        "pairs": 11,
        "dayChangePct": 0
      },
      {
        "day": "2026-07-22",
        "index": 100,
        "pairs": 12,
        "dayChangePct": 0
      },
      {
        "day": "2026-07-23",
        "index": 100,
        "pairs": 12,
        "dayChangePct": 0
      },
      {
        "day": "2026-07-24",
        "index": 100,
        "pairs": 12,
        "dayChangePct": 0
      },
      {
        "day": "2026-07-25",
        "index": 100,
        "pairs": 12,
        "dayChangePct": 0
      },
      {
        "day": "2026-07-26",
        "index": 100,
        "pairs": 12,
        "dayChangePct": 0
      },
      {
        "day": "2026-07-27",
        "index": 100,
        "pairs": 12,
        "dayChangePct": 0
      },
      {
        "day": "2026-07-28",
        "index": 100,
        "pairs": 12,
        "dayChangePct": 0
      },
      {
        "day": "2026-07-29",
        "index": 100,
        "pairs": 12,
        "dayChangePct": 0
      },
      {
        "day": "2026-07-30",
        "index": 100,
        "pairs": 12,
        "dayChangePct": 0
      },
      {
        "day": "2026-07-31",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-01",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-02",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-03",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-04",
        "index": 100,
        "pairs": 14,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-05",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-06",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-07",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-08",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-09",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-10",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-11",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-12",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-13",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-14",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-15",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-16",
        "index": 100,
        "pairs": 13,
        "dayChangePct": 0
      },
      {
        "day": "2026-08-17",
        "index": 100,
        "pairs": 14,
        "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": "aegisagent",
      "name": "Aegis Autonomous AI Agent Platform",
      "url": "https://aegisagent.ai/",
      "short_summary": "Autonomously decomposes and executes user-defined goals: web research, content generation, email triage, code review, monitoring, and workflow orchestration",
      "price": {
        "observed": true,
        "billing": "subscription",
        "lowest_monthly_usd": 50,
        "monthly_usd": 50,
        "headline": "From $50/mo",
        "summary": "From $50/mo. Aegis publicly displays a monthly price of $50, with no additional plan details visible in the supplied homepage context."
      },
      "evidence_quality": "high",
      "upvotes": 0
    },
    {
      "agent_id": "azure_foundry_deep_research",
      "name": "Deep Research API",
      "url": "https://azure.microsoft.com/en-us/blog/introducing-deep-research-in-azure-ai-foundry-agent-service/",
      "short_summary": "Automates web-scale research—plans, analyzes, and synthesizes information from across the web to produce traceable, source-backed research reports",
      "price": {
        "observed": false,
        "billing": "not_found",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "The supplied pages identify Azure product pricing resources but do not show a reliable public subscription price for this offering."
      },
      "evidence_quality": "high",
      "upvotes": 0
    },
    {
      "agent_id": "deep_research_max",
      "name": "Deep Research Max",
      "url": "https://blog.google/innovation-and-ai/models-and-research/gemini-models/next-generation-gemini-deep-research/",
      "short_summary": "performs autonomous long-horizon research, generating comprehensive, fully-cited analytical reports by blending web search with proprietary data sources",
      "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 Deep Research or Deep Research Max in the supplied pages."
      },
      "evidence_quality": "high",
      "upvotes": 0
    },
    {
      "agent_id": "exa",
      "name": "Exa Deep Research API",
      "url": "https://exa.ai/",
      "short_summary": "Provides web search, crawling, and research for AI agents; runs searches across verticals and deep research tasks returning structured results with citations",
      "price": {
        "observed": true,
        "billing": "usage",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "Paid (price not published)",
        "summary": "Exa publishes usage-based pricing for search, agent runs, content retrieval, deep search, monitors, and related usage components rather than fixed monthly plans."
      },
      "evidence_quality": "high",
      "upvotes": 0
    },
    {
      "agent_id": "examples",
      "name": "Examples",
      "url": "https://github.com/NVIDIA-AI-Blueprints/aiq-research-assistant",
      "short_summary": "Performs agentic research, producing quick cited answers and in-depth report-style research with multi-step planning",
      "price": {
        "observed": false,
        "billing": "not_found",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "No public pricing was found for the NVIDIA AIQ research assistant repository."
      },
      "evidence_quality": "high",
      "upvotes": 0
    },
    {
      "agent_id": "fact_ai",
      "name": "FactsAI",
      "url": "https://factsai.org/",
      "short_summary": "performs AI-powered research and returns answers with citations from across the web via an API",
      "price": {
        "observed": true,
        "billing": "usage",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "Paid (price not published)",
        "summary": "FactsAI offers credit bundles with no required subscription, charging $0.012 per request across Starter, Growth, and Scale options."
      },
      "evidence_quality": "high",
      "upvotes": 0
    },
    {
      "agent_id": "firecrawl_agent",
      "name": "Firecrawl Agent Stack",
      "url": "https://www.firecrawl.dev/blog/firecrawl-agent-open-source",
      "short_summary": "autonomous web research and structured data extraction; builds and deploys custom web research agents using a plan-act loop with parallel sub-agents",
      "price": {
        "observed": false,
        "billing": "subscription",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "The pricing page indicates subscription plans such as Hobby, Standard, and Growth, with publicly displayed euro-denominated prices, but the supplied context does not associate specific prices with individual plans."
      },
      "evidence_quality": "high",
      "upvotes": 0
    },
    {
      "agent_id": "google_deep_research",
      "name": "Gemini Deep Research Agent",
      "url": "https://ai.google.dev/gemini-api/docs/interactions/deep-research",
      "short_summary": "autonomously plans, executes, and synthesizes multi-step research tasks to produce detailed, cited reports",
      "price": {
        "observed": true,
        "billing": "freemium",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "Free tier + paid plans (price not published)",
        "summary": "Gemini API offers a permanent free tier, usage-based paid access, and an enterprise tier priced through sales."
      },
      "evidence_quality": "high",
      "upvotes": 0
    },
    {
      "agent_id": "openai_deep_research",
      "name": "OpenAI Deep Research API",
      "url": "https://developers.openai.com/cookbook/examples/deep_research_api/introduction_to_deep_research_api_agents",
      "short_summary": "performs deep multi-step empirical research, synthesis, planning, and tool use via agentic research workflows",
      "price": {
        "observed": true,
        "billing": "usage",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "Paid (price not published)",
        "summary": "OpenAI API pricing is usage-based, with the documented deep-research example using gpt-5.6-terra at $2.00 per 1M standard input tokens and $12.00 per 1M standard output tokens."
      },
      "evidence_quality": "high",
      "upvotes": 0
    },
    {
      "agent_id": "researchapi_ai",
      "name": "AI Research API",
      "url": "https://researchapi.ai/",
      "short_summary": "generates AI-powered research reports on any topic by scouring the web and compiling findings into markdown-formatted reports with sources",
      "price": {
        "observed": false,
        "billing": "unknown",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "No public price found on the vendor site."
      },
      "evidence_quality": "high",
      "upvotes": 0
    }
  ],
  "platforms_also_here": [
    {
      "agent_id": "aurix_agent",
      "name": "Aurix Agent",
      "url": "https://haikzs.tech",
      "short_summary": "Open-source terminal AI agent for coding, browser automation, deep research, bug hunting, and multi-agent workflows. Runs via CLI, Discord, Telegram, or WhatsA…",
      "price": {
        "observed": false,
        "billing": "not_found",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "No public pricing is shown on the homepage, and no pricing page was available."
      },
      "home_niche": "cli-coding-agent",
      "also_covers": true,
      "upvotes": 0
    },
    {
      "agent_id": "brightwave",
      "name": "Brightwave",
      "url": "https://brightwave.io/",
      "short_summary": "Enterprise AI platform with autonomous agents that collaborate on complex projects. Provides unlimited scope and context, full sourcing and verifiability, and…",
      "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": "enterprise-ai-platform",
      "also_covers": true,
      "upvotes": 0
    },
    {
      "agent_id": "exa_ai",
      "name": "Exa",
      "url": "https://exa.ai/",
      "short_summary": "provides web search, crawling, and research capabilities for AI agents; extracts structured content and enrichments from websites and live data",
      "price": {
        "observed": true,
        "billing": "usage",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "Paid (price not published)",
        "summary": "Exa publishes usage-based API pricing, with endpoint rates starting at $1 per 1k pages and $7 per 1k search requests, plus per-run and enrichment charges."
      },
      "home_niche": "web-search-api",
      "also_covers": true,
      "upvotes": 0
    },
    {
      "agent_id": "gemini_ai",
      "name": "Gemini",
      "url": "https://gemini.google/us/about/?hl=en",
      "short_summary": "Everyday AI assistant that helps with tasks at work, school or home, including image/video generation, deep research, breaking goals into steps, daily briefing…",
      "price": {
        "observed": true,
        "billing": "freemium",
        "lowest_monthly_usd": 4.99,
        "monthly_usd": 4.99,
        "headline": "Free tier, then from $4.99/mo",
        "summary": "Free tier, then from $4.99/mo. Google Gemini offers a permanent free tier plus Google AI Plus at $4.99 per month and Google AI Pro at $19.99 per month, with two additional monthly prices shown without plan details."
      },
      "home_niche": "personal-ai-assistant",
      "also_covers": true,
      "upvotes": 0
    },
    {
      "agent_id": "kendr",
      "name": "Kendr",
      "url": "https://kendr.org",
      "short_summary": "Workspace for deep research, agentic workflows, and reusable knowledge bases. Integrates research, multi-step agent execution, approvals, and persistent contex…",
      "price": {
        "observed": true,
        "billing": "subscription",
        "lowest_monthly_usd": 10,
        "monthly_usd": 10,
        "headline": "From $10/mo",
        "summary": "From $10/mo. Kendr offers monthly credit plans from $10 to $150, plus non-expiring usage-based credit top-ups."
      },
      "home_niche": "enterprise-knowledge-platform",
      "also_covers": true,
      "upvotes": 0
    },
    {
      "agent_id": "manifold_ai",
      "name": "Manifold Ai",
      "url": "https://manifold.ai/platform/ai-agents",
      "short_summary": "Orchestrates domain-specialized AI agents to accelerate scientific research—generating cohorts, tables, visualizations, exploring datasets, estimating cohort s…",
      "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": "autonomous-ai-research-lab",
      "also_covers": true,
      "upvotes": 0
    },
    {
      "agent_id": "skywork_ai",
      "name": "Skywork",
      "url": "https://skywork.ai/",
      "short_summary": "Generates multimodal content (documents, slides, sheets, images, websites, videos, podcasts) from simple input, including deep research, and records/transcribe…",
      "price": {
        "observed": false,
        "billing": "not_found",
        "lowest_monthly_usd": null,
        "monthly_usd": null,
        "headline": "No public price found",
        "summary": "No public pricing was visible on the supplied Skywork homepage, and no pricing page was available."
      },
      "home_niche": "meeting-notes-transcription",
      "also_covers": true,
      "upvotes": 0
    }
  ],
  "page_url": "https://agentery.com/market/deep-research-agent",
  "summary": {
    "niche": "deep-research-agent",
    "sector": "research-knowledge-work",
    "pricing_by_provider_type": {
      "headline": "Prices differ by provider type and buyer tier — no blended headline is used. Strongest cohort: Agents · Pro median $29/mo (6 providers). See benchmarks_by_provider_type_and_tier for the full matrix.",
      "benchmarks": [
        {
          "provider_type": "agent",
          "provider_type_label": "Agents",
          "buyer_tier": "pro",
          "buyer_tier_label": "Pro",
          "pricing_unit": "flat",
          "pricing_unit_label": "flat monthly",
          "comparable_provider_count": 6,
          "reliability": "medium",
          "median": 29.24,
          "p25": 26,
          "p75": 44.87,
          "status": "ok"
        },
        {
          "provider_type": "agent",
          "provider_type_label": "Agents",
          "buyer_tier": "individual",
          "buyer_tier_label": "Individual",
          "pricing_unit": "flat",
          "pricing_unit_label": "flat monthly",
          "comparable_provider_count": 2,
          "reliability": "low",
          "median": null,
          "p25": null,
          "p75": null,
          "status": "observed_offers_only",
          "observed_offers": [
            19,
            20
          ]
        }
      ],
      "warnings": [
        "This niche currently has sufficient agent pricing but insufficient MCP pricing."
      ],
      "full_pricing_via": {
        "tool": "price_benchmark",
        "arguments": {
          "niche": "deep-research-agent"
        },
        "note": "add provider_type + buyer_tier for a specific cohort"
      }
    },
    "page_url": "https://agentery.com/market/deep-research-agent",
    "counts": {
      "listings_with_price_capture": 55,
      "listings_with_observed_public_price": 23,
      "providers_with_numeric_monthly_price_latest_scan": 10,
      "like_for_like_comparable_pairs": 9
    },
    "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": "ok",
    "pricing_by_tier": [
      {
        "tier": "individual",
        "currency": "USD",
        "period": "month",
        "unit": "flat",
        "median": 20,
        "provider_count": 3,
        "plan_observation_count": 3,
        "data_confidence": 0.23,
        "data_confidence_basis": {
          "provider_component": 0.25,
          "observation_component": 0.15,
          "provider_count": 3,
          "plan_observation_count": 3
        },
        "reliability": "low",
        "members": [
          {
            "provider": "research_master",
            "usd": 19
          },
          {
            "provider": "managed_research",
            "usd": 20
          },
          {
            "provider": "fact_check",
            "usd": 99
          }
        ]
      },
      {
        "tier": "pro",
        "currency": "USD",
        "period": "month",
        "unit": "flat",
        "median": 29,
        "provider_count": 7,
        "plan_observation_count": 9,
        "data_confidence": 0.56,
        "data_confidence_basis": {
          "provider_component": 0.58,
          "observation_component": 0.45,
          "provider_count": 7,
          "plan_observation_count": 9
        },
        "reliability": "medium",
        "members": [
          {
            "provider": "fact_check",
            "usd": 7.99
          },
          {
            "provider": "mirothinker",
            "usd": 19
          },
          {
            "provider": "ninjatech_research",
            "usd": 25
          },
          {
            "provider": "research_master",
            "usd": 29
          },
          {
            "provider": "noteweave",
            "usd": 29.49
          },
          {
            "provider": "aegisagent",
            "usd": 50
          },
          {
            "provider": "unforgeapi",
            "usd": 114.5
          }
        ],
        "p25": 22,
        "p75": 39.74
      },
      {
        "tier": "team_sme",
        "currency": "USD",
        "period": "month",
        "unit": "flat",
        "median": 224.5,
        "provider_count": 2,
        "plan_observation_count": 2,
        "data_confidence": 0.15,
        "data_confidence_basis": {
          "provider_component": 0.17,
          "observation_component": 0.1,
          "provider_count": 2,
          "plan_observation_count": 2
        },
        "reliability": "low",
        "members": [
          {
            "provider": "ninjatech_research",
            "usd": 50
          },
          {
            "provider": "fact_check",
            "usd": 399
          }
        ]
      }
    ],
    "pricing_coverage": {
      "listings_with_price_capture": 55,
      "listings_with_observed_public_price": 23,
      "normalized_observations": 15,
      "comparable_providers": 9,
      "strict_cohorts": 3,
      "exclusion_reasons": {
        "ambiguous_cadence": 5,
        "one_time": 2,
        "usage_not_monthly": 22,
        "range": 4
      }
    },
    "pricing_note": "Provider-deduped, FX-normalized monthly medians, separated by buyer tier AND billing unit (flat/per_seat/per_user/per_agent) — incompatible units are never blended. Ranges (p25/p75) only at >=5 providers; data_confidence is provider-count-weighted. Usage-metered, promo, range, one-time and ambiguous-cadence plans are excluded.",
    "pricing_excluded_observations": {
      "ambiguous_cadence": 5,
      "one_time": 2,
      "usage_not_monthly": 22,
      "range": 4
    },
    "billing_mix": {
      "freemium": 10,
      "free": 6,
      "usage": 6,
      "subscription": 1
    },
    "free_tier_share": 0.7,
    "top_providers": [
      {
        "agent_id": "aegisagent",
        "name": "Aegis Autonomous AI Agent Platform",
        "price": {
          "observed": true,
          "billing": "subscription",
          "lowest_monthly_usd": 50,
          "monthly_usd": 50,
          "headline": "From $50/mo",
          "summary": "From $50/mo. Aegis publicly displays a monthly price of $50, with no additional plan details visible in the supplied homepage context."
        },
        "observed": true
      },
      {
        "agent_id": "azure_foundry_deep_research",
        "name": "Deep Research API",
        "price": {
          "observed": false,
          "billing": "not_found",
          "lowest_monthly_usd": null,
          "monthly_usd": null,
          "headline": "No public price found",
          "summary": "The supplied pages identify Azure product pricing resources but do not show a reliable public subscription price for this offering."
        },
        "observed": false
      },
      {
        "agent_id": "deep_research_max",
        "name": "Deep Research Max",
        "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 Deep Research or Deep Research Max in the supplied pages."
        },
        "observed": false
      },
      {
        "agent_id": "exa",
        "name": "Exa Deep Research API",
        "price": {
          "observed": true,
          "billing": "usage",
          "lowest_monthly_usd": null,
          "monthly_usd": null,
          "headline": "Paid (price not published)",
          "summary": "Exa publishes usage-based pricing for search, agent runs, content retrieval, deep search, monitors, and related usage components rather than fixed monthly plans."
        },
        "observed": true
      },
      {
        "agent_id": "examples",
        "name": "Examples",
        "price": {
          "observed": false,
          "billing": "not_found",
          "lowest_monthly_usd": null,
          "monthly_usd": null,
          "headline": "No public price found",
          "summary": "No public pricing was found for the NVIDIA AIQ research assistant repository."
        },
        "observed": false
      }
    ],
    "suggested_next_calls": [
      {
        "tool": "price_benchmark",
        "arguments": {
          "niche": "deep-research-agent"
        },
        "purpose": "full observed price distribution + per-tier medians for this niche"
      },
      {
        "tool": "niche_report",
        "arguments": {
          "niche": "deep-research-agent",
          "response_mode": "full"
        },
        "purpose": "the complete report incl. index series and tier decomposition"
      },
      {
        "tool": "suggest_alternatives",
        "arguments": {
          "agent_id": "aegisagent"
        },
        "purpose": "comparable (optionally cheaper) providers to a named agent"
      },
      {
        "tool": "get_agent_profile",
        "arguments": {
          "agent_id": "aegisagent"
        },
        "purpose": "full profile, integrations and pricing for one provider"
      }
    ]
  }
}