Autonomous AI Research Lab
Query this niche via MCP
market_report({ query: "Autonomous AI Research Lab", response_mode: "summary" })Agents · median
$224/mo
MCP servers · median
All plans — Agents vs MCPs
each dot = one provider · log scaleAgents $224
aster · $60
K Dense · $199
Luma Agent · $224
K Dense · $499
$50
$100
$250
$500
AgentsMCP serversshaded = middle half · line = median
All plans
4 pricedProvidervs its cohort medianMonthly
asteragent
$60 below
K Denseagent
$199 below
Luma Agentagent
$224 ~median
K Denseagent
$499 above
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 Autonomous AI Research Lab (latest observation 2026-10-15T03:43:03.005Z). 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": "autonomous-ai-research-lab",
"parent_sector": "research-knowledge-work",
"provider_type_pricing": {
"slug": "autonomous-ai-research-lab",
"pricing_basis": "lowest_observed_monthly_usd",
"provider_type_methodology": "commercial-form-v2",
"provider_type_methodology_published_at": "2026-07-31",
"blended": {
"median": 199,
"p25": null,
"p75": null,
"providers": 3
},
"by_provider_type": {
"agent": {
"median": 199,
"p25": null,
"p75": null,
"providers": 3,
"publishable": true,
"confidence": "provisional"
},
"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": "emerging",
"observed_node_count": 4,
"adjacent_niches": [
"expert-call-summarisation",
"business-research-enrichment",
"literature-review",
"news-monitoring-agent",
"company-intelligence-agent",
"document-qa-agent"
],
"market_pulse": {
"pulse": 56,
"drivers": [
"enterprise money present"
],
"price_move_30d_pct": null,
"money_share": 0.4,
"entry_rate": 0,
"alive_share": 0.9666666666666667
},
"price_move": {
"d_pct": 0,
"w_pct": 0,
"m_pct": 0,
"comparable_agents": 2,
"quarantined_agents": 0,
"confidence": "thin",
"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,
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,
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,
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,
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": 1,
"pro": 2,
"team_sme": 1,
"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": 28,
"observed": 5,
"byPersona": {
"free": {
"n": 4,
"nPriced": 0,
"reliability": "none",
"median": null,
"p25": null,
"p75": null,
"min": null,
"max": null,
"mean": null,
"stdev": null,
"usageShare": 0.25
},
"individual": {
"n": 0,
"nPriced": 0,
"reliability": "none",
"median": null,
"p25": null,
"p75": null,
"min": null,
"max": null,
"mean": null,
"stdev": null,
"usageShare": 0
},
"pro": {
"n": 5,
"nPriced": 5,
"reliability": "medium",
"median": 29,
"p25": 20,
"p75": 100,
"min": 9,
"max": 199,
"mean": 71.4,
"stdev": 79.74,
"usageShare": 0.4
},
"team_sme": {
"n": 3,
"nPriced": 3,
"reliability": "low",
"median": 249,
"p25": 224,
"p75": 374,
"min": 199,
"max": 499,
"mean": 315.67,
"stdev": 160.73,
"usageShare": 0
},
"enterprise": {
"n": 2,
"nPriced": 0,
"reliability": "none",
"median": null,
"p25": null,
"p75": null,
"min": null,
"max": null,
"mean": null,
"stdev": null,
"usageShare": 0
}
},
"byPersonaMonthly": {
"free": {
"nMonthly": 0,
"p25": null,
"median": null,
"p75": null,
"confidence": "none",
"usageShare": 0.25,
"mixedBilling": true,
"monthlyComparable": false
},
"individual": {
"nMonthly": 0,
"p25": null,
"median": null,
"p75": null,
"confidence": "none",
"usageShare": 0,
"mixedBilling": false,
"monthlyComparable": false
},
"pro": {
"nMonthly": 3,
"p25": 60,
"median": 100,
"p75": 149.5,
"confidence": "low",
"usageShare": 0.4,
"mixedBilling": true,
"monthlyComparable": true
},
"team_sme": {
"nMonthly": 3,
"p25": 224,
"median": 249,
"p75": 374,
"confidence": "low",
"usageShare": 0,
"mixedBilling": false,
"monthlyComparable": true
},
"enterprise": {
"nMonthly": 0,
"p25": null,
"median": null,
"p75": null,
"confidence": "none",
"usageShare": 0,
"mixedBilling": false,
"monthlyComparable": false
}
},
"byTierCohorts": {
"status": "ok",
"cohorts": [
{
"tier": "pro",
"currency": "USD",
"period": "month",
"unit": "flat",
"median": 129.5,
"provider_count": 2,
"plan_observation_count": 3,
"data_confidence": 0.16,
"data_confidence_basis": {
"provider_component": 0.17,
"observation_component": 0.15,
"provider_count": 2,
"plan_observation_count": 3
},
"reliability": "low",
"members": [
{
"provider": "aster",
"usd": 60
},
{
"provider": "k_dense",
"usd": 199
}
]
},
{
"tier": "team_sme",
"currency": "USD",
"period": "month",
"unit": "flat",
"median": 361.5,
"provider_count": 2,
"plan_observation_count": 3,
"data_confidence": 0.16,
"data_confidence_basis": {
"provider_component": 0.17,
"observation_component": 0.15,
"provider_count": 2,
"plan_observation_count": 3
},
"reliability": "low",
"members": [
{
"provider": "luma_agent",
"usd": 224
},
{
"provider": "k_dense",
"usd": 499
}
]
}
],
"rejected": {
"ambiguous_cadence": 2,
"usage_not_monthly": 2
},
"evidence": {
"status": "ok",
"single_observations": [],
"observed_offers": [
{
"billing": "monthly",
"unit": "flat",
"count": 6,
"offers": [
{
"provider": "aster",
"tier": "pro",
"billing": "monthly",
"unit": "flat",
"price": "$20 per month",
"monthly_usd": 20
},
{
"provider": "aster",
"tier": "pro",
"billing": "monthly",
"unit": "flat",
"price": "$100 per month",
"monthly_usd": 100
},
{
"provider": "k_dense",
"tier": "pro",
"billing": "monthly",
"unit": "flat",
"price": "$199 /month",
"monthly_usd": 199
},
{
"provider": "k_dense",
"tier": "team_sme",
"billing": "monthly",
"unit": "flat",
"price": "$499 /month",
"monthly_usd": 499
},
{
"provider": "luma_agent",
"tier": "team_sme",
"billing": "monthly",
"unit": "flat",
"price": "$199/month",
"monthly_usd": 199
},
{
"provider": "luma_agent",
"tier": "team_sme",
"billing": "monthly",
"unit": "flat",
"price": "$249.00/month",
"monthly_usd": 249
}
]
},
{
"billing": "usage",
"unit": "other_usage",
"count": 2,
"offers": [
{
"provider": "k_dense",
"tier": "pro",
"billing": "usage",
"unit": "other_usage",
"price": "$9 per run",
"monthly_usd": null
},
{
"provider": "k_dense",
"tier": "pro",
"billing": "usage",
"unit": "other_usage",
"price": "$29 per run",
"monthly_usd": null
}
]
},
{
"billing": "unspecified_period",
"unit": "flat",
"count": 2,
"offers": [
{
"provider": "aster",
"tier": "enterprise",
"billing": "unspecified_period",
"unit": "flat",
"price": "Custom",
"monthly_usd": null
},
{
"provider": "k_dense",
"tier": "enterprise",
"billing": "unspecified_period",
"unit": "flat",
"price": "Custom",
"monthly_usd": null
}
]
}
],
"coverage": {
"priced_providers": 3,
"normalized_observations": 6,
"comparable_providers": 3,
"strict_cohorts": 2,
"exclusion_reasons": {
"ambiguous_cadence": 2,
"usage_not_monthly": 2
}
}
}
},
"quoteOnlyProvidersByTier": {
"pro": 0,
"enterprise": 2,
"team_sme": 0
},
"billingMix": {
"freemium": 2,
"free": 2,
"subscription": 1
},
"freeTierShare": 0.8,
"medianLowestUsd": 199
},
"movement": {
"niche": "autonomous-ai-research-lab",
"sector": "research-knowledge-work",
"pricedNow": 3,
"pairs": 2,
"repriced": [],
"newlyPriced": [
"luma_agent"
],
"droppedFromPriced": [],
"likeForLikePct": 0,
"kind": "composition",
"narrative": "Composition change (average moved, but no agent changed its price): 1 newly published pricing."
},
"index_series": {
"series": [
{
"day": "2026-09-16",
"index": 100,
"pairs": 4,
"dayChangePct": 0
},
{
"day": "2026-09-17",
"index": 100,
"pairs": 4,
"dayChangePct": 0
},
{
"day": "2026-09-18",
"index": 100,
"pairs": 4,
"dayChangePct": 0
},
{
"day": "2026-09-19",
"index": 100,
"pairs": 4,
"dayChangePct": 0
},
{
"day": "2026-09-20",
"index": 100,
"pairs": 4,
"dayChangePct": 0
},
{
"day": "2026-09-21",
"index": 100,
"pairs": 4,
"dayChangePct": 0
},
{
"day": "2026-09-22",
"index": 100,
"pairs": 4,
"dayChangePct": 0
},
{
"day": "2026-09-23",
"index": 100,
"pairs": 4,
"dayChangePct": 0
},
{
"day": "2026-09-24",
"index": 100,
"pairs": 4,
"dayChangePct": 0
},
{
"day": "2026-09-25",
"index": 100,
"pairs": 4,
"dayChangePct": 0
},
{
"day": "2026-09-26",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-09-27",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-09-28",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-09-29",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-09-30",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-01",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-02",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-03",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-04",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-05",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-06",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-07",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-08",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-09",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-10",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-11",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-12",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-13",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-14",
"index": 100,
"pairs": 3,
"dayChangePct": 0
},
{
"day": "2026-10-15",
"index": 100,
"pairs": 3,
"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": "agentic_ai_for_lab_automation_",
"name": "Agentic Ai For Lab Automation",
"url": "https://qpillars.com/agentic-ai/lab-automation",
"short_summary": "Orchestrates multi-step laboratory workflows including sample prep, plate handling, instrument scheduling, and protocols by planning, validating, and executing…",
"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 QPillars Agentic AI for Lab Automation."
},
"evidence_quality": "high",
"upvotes": 0
},
{
"agent_id": "aris",
"name": "ARIS (Auto-Research-In-Sleep)",
"url": "https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep",
"short_summary": "autonomous ML research workflow — plans, drafts, runs experiments, scores papers, identifies weaknesses, and rewrites narrative using cross-model adversarial r…",
"price": {
"observed": false,
"billing": "not_found",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public pricing or paid plan details were observed in the supplied homepage context."
},
"evidence_quality": "high",
"upvotes": 0
},
{
"agent_id": "autoresearch",
"name": "AutoResearch",
"url": "https://github.com/karpathy/autoresearch",
"short_summary": "autonomously experiments with LLM training code—modifies architecture, hyperparameters, and optimizer, trains for a 5-minute budget, evaluates, and keeps or di…",
"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 this open-source GitHub repository."
},
"evidence_quality": "high",
"upvotes": 0
},
{
"agent_id": "bios",
"name": "Bios",
"url": "https://ai.bio.xyz/",
"short_summary": "performs biomedical research tasks via literature analysis and data analysis, orchestrating specialized subagents",
"price": {
"observed": false,
"billing": "not_found",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public subscription or usage plans are listed; the homepage only references estimated compute costs of under $7 or about $8 per design run."
},
"evidence_quality": "medium",
"upvotes": 0
},
{
"agent_id": "deepmind",
"name": "Deepmind",
"url": "https://deepmind.google/",
"short_summary": "Conducts frontier AI research and builds AI models for content generation, scientific discovery, and agentic action (e.g. Gemini, AlphaFold, image/video/music…",
"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": "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."
},
"evidence_quality": "medium",
"upvotes": 0
},
{
"agent_id": "aster",
"name": "Aster",
"url": "https://asterlab.ai/",
"short_summary": "conducts autonomous AI research and experimentation, including optimization of code and LLMs",
"price": {
"commercial": {
"entry_offer": {
"line": "Pro",
"monthly_native": 20,
"monthly_usd": 20,
"commitment": "monthly",
"basis": "$20/month",
"billing_verified": true
},
"currency": "USD",
"lines": [
{
"name": "Free",
"price": "$0",
"kind": "free",
"billed": "monthly"
},
{
"name": "Pro",
"price": "$20 per month",
"kind": "base_subscription",
"billed": "monthly"
},
{
"name": "Max",
"price": "$100 per month",
"kind": "base_subscription",
"billed": "monthly"
},
{
"name": "Enterprise",
"price": "Custom",
"kind": "custom"
}
]
},
"observed": true,
"billing": "freemium",
"lowest_monthly_usd": 20,
"monthly_usd": 20,
"headline": "Free plan; paid from $20/mo",
"summary": "Free plan; paid from $20/mo. Aster offers a free plan, Pro at $20 per month, Max at $100 per month, and custom Enterprise pricing."
},
"evidence_quality": "low",
"upvotes": 0
},
{
"agent_id": "deepresearch_bench",
"name": "Deepresearch Bench",
"url": "https://huggingface.co/spaces/muset-ai/DeepResearch-Bench-Leaderboard",
"short_summary": "hosts a benchmark leaderboard for deep research AI models",
"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": "low",
"upvotes": 0
},
{
"agent_id": "dotmatics_luma",
"name": "Luma AI Co-scientist",
"url": "https://www.dotmatics.com/luma",
"short_summary": "Manages, normalizes, and structures scientific R&D data and runs adaptive scientific workflows; provides AI-driven decision support for research",
"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": "low",
"upvotes": 0
},
{
"agent_id": "hillclimb",
"name": "Hillclimb",
"url": "https://hillclimb.com/",
"short_summary": "aggregates human research data and automates RL environment creation to produce training data for AI models",
"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": "low",
"upvotes": 0
}
],
"platforms_also_here": [
{
"agent_id": "bitterbot",
"name": "Bitterbot",
"url": "https://bitterbot.ai",
"short_summary": "Open-source AI agent for research, data analysis, and task automation. Features P2P mesh networking, skill marketplace, and distributed intelligence with biolo…",
"price": {
"observed": false,
"billing": "not_found",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public pricing or paid plan details were observed on the homepage."
},
"home_niche": "agent-framework-open-source",
"also_covers": true,
"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": {
"commercial": {
"entry_offer": {
"line": "Hobby",
"monthly_native": 19,
"monthly_usd": 19,
"commitment": "monthly",
"basis": "$19/month",
"billing_verified": true
},
"annual_option": {
"line": "Hobby (annual billing)",
"monthly_equivalent_native": 16,
"total_native": 192
},
"currency": "USD",
"lines": [
{
"name": "Free",
"price": "Free",
"kind": "free",
"billed": "monthly"
},
{
"name": "Hobby",
"price": "$19/month billed monthly",
"kind": "base_subscription",
"billed": "monthly"
},
{
"name": "Hobby (annual billing)",
"price": "$16/month billed annually",
"kind": "base_subscription",
"billed": "annually"
}
]
},
"observed": true,
"billing": "freemium",
"lowest_monthly_usd": 19,
"monthly_usd": 19,
"headline": "Free plan; paid from $19/mo; $16/mo equivalent billed annually",
"summary": "Free plan; paid from $19/mo; $16/mo equivalent billed annually. Firecrawl offers a free tier with 1,000 monthly credits and a Hobby subscription starting at $19/month, or $16/month billed annually."
},
"home_niche": "deep-research-agent",
"also_covers": true,
"upvotes": 0
},
{
"agent_id": "lingtrade",
"name": "Lingtrade",
"url": "https://github.com/novalgo-x/LingTrade",
"short_summary": "Open-source multi-agent AI research workstation for A-share stock analysis. Features collaborative agent-based research, simulated trading loop, custom knowled…",
"price": {
"observed": false,
"billing": "not_found",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public pricing or explicit free-use terms were observed for LingTrade."
},
"home_niche": "quantitative-analysis-agent",
"also_covers": true,
"upvotes": 0
},
{
"agent_id": "mirothinker",
"name": "Mirothinker",
"url": "https://miromind.ai/",
"short_summary": "deep research and prediction for complex tasks across domains (e.g. research, failure analysis, hypothesis generation, contract analysis, risk modeling)",
"price": {
"commercial": {
"entry_offer": {
"line": "Pro",
"monthly_native": 19,
"monthly_usd": 19,
"commitment": "monthly",
"basis": "$19/month",
"billing_verified": false,
"billing_note": "the pricing page has a \"Monthly Yearly (save 16%)\" toggle and only one state was captured; this may be the annual-billing rate, so the month-to-month price is not verified"
},
"currency": "USD",
"notes": [
"other prices: Starter Boost $4.99 (one-time)",
"billing period unverified: the pricing page has a \"Monthly Yearly (save 16%)\" toggle and only one state was captured; this may be the annual-billing rate, so the month-to-month price is not verified"
],
"lines": [
{
"name": "Free",
"price": "$0/month",
"kind": "free",
"billed": "monthly"
},
{
"name": "Pro",
"price": "$19/month",
"kind": "base_subscription",
"billed": "monthly"
},
{
"name": "Starter Boost",
"price": "$4.99",
"kind": "one_off",
"billed": "one_off"
}
]
},
"observed": true,
"billing": "freemium",
"lowest_monthly_usd": 19,
"monthly_usd": 19,
"headline": "Free plan; paid from $19/mo (billing period unverified: page has a Monthly/Annual toggle)",
"summary": "Free plan; paid from $19/mo (billing period unverified: page has a Monthly/Annual toggle). MiroMind offers a freemium model with a free tier (100 daily credits) and a Pro subscription at $19/month (20,000 monthly credits), plus one-time credit boost packs."
},
"home_niche": "deep-research-agent",
"also_covers": true,
"upvotes": 0
},
{
"agent_id": "morphmind",
"name": "Morphmind",
"url": "https://morphmind.ai",
"short_summary": "Platform for building controllable AI agents with full visibility and reproducibility. Offers AgentLab (no-code agent builder), Caliper (lab automation), and M…",
"price": {
"commercial": {
"entry_offer": {
"line": "Essential",
"monthly_native": 29,
"monthly_usd": 29,
"commitment": "monthly",
"basis": "$29/month",
"billing_verified": true
},
"currency": "USD",
"lines": [
{
"name": "Free",
"price": "$0 /mo",
"kind": "free",
"billed": "monthly"
},
{
"name": "Essential",
"price": "$29 /mo",
"kind": "base_subscription",
"billed": "monthly"
},
{
"name": "Pro",
"price": "$49 /mo",
"kind": "base_subscription",
"billed": "monthly"
},
{
"name": "Max",
"price": "$129 /mo",
"kind": "base_subscription",
"billed": "monthly"
}
]
},
"observed": true,
"billing": "freemium",
"lowest_monthly_usd": 29,
"monthly_usd": 29,
"headline": "Free plan; paid from $29/mo",
"summary": "Free plan; paid from $29/mo. MorphMind offers a permanent free plan and three paid individual monthly plans priced from $29 to $129 per month."
},
"home_niche": "agent-builder-no-code",
"also_covers": true,
"upvotes": 0
}
],
"page_url": "https://agentery.com/market/autonomous-ai-research-lab",
"summary": {
"niche": "autonomous-ai-research-lab",
"sector": "research-knowledge-work",
"pricing_by_provider_type": {
"headline": "No published benchmark for autonomous-ai-research-lab yet — too few comparable priced providers. Observed offers are listed.",
"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": 2,
"reliability": "low",
"median": null,
"p25": null,
"p75": null,
"status": "observed_offers_only",
"observed_offers": [
60,
199
]
},
{
"provider_type": "agent",
"provider_type_label": "Agents",
"buyer_tier": "team_sme",
"buyer_tier_label": "Team / SME",
"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": [
224,
499
]
}
],
"warnings": [],
"full_pricing_via": {
"tool": "price_benchmark",
"arguments": {
"niche": "autonomous-ai-research-lab"
},
"note": "add provider_type + buyer_tier for a specific cohort"
}
},
"page_url": "https://agentery.com/market/autonomous-ai-research-lab",
"counts": {
"listings_with_price_capture": 28,
"listings_with_observed_public_price": 5,
"providers_with_numeric_monthly_price_latest_scan": 3,
"like_for_like_comparable_pairs": 2
},
"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": "pro",
"currency": "USD",
"period": "month",
"unit": "flat",
"median": 129.5,
"provider_count": 2,
"plan_observation_count": 3,
"data_confidence": 0.16,
"data_confidence_basis": {
"provider_component": 0.17,
"observation_component": 0.15,
"provider_count": 2,
"plan_observation_count": 3
},
"reliability": "low",
"members": [
{
"provider": "aster",
"usd": 60
},
{
"provider": "k_dense",
"usd": 199
}
]
},
{
"tier": "team_sme",
"currency": "USD",
"period": "month",
"unit": "flat",
"median": 361.5,
"provider_count": 2,
"plan_observation_count": 3,
"data_confidence": 0.16,
"data_confidence_basis": {
"provider_component": 0.17,
"observation_component": 0.15,
"provider_count": 2,
"plan_observation_count": 3
},
"reliability": "low",
"members": [
{
"provider": "luma_agent",
"usd": 224
},
{
"provider": "k_dense",
"usd": 499
}
]
}
],
"pricing_coverage": {
"listings_with_price_capture": 28,
"listings_with_observed_public_price": 5,
"normalized_observations": 6,
"comparable_providers": 3,
"strict_cohorts": 2,
"exclusion_reasons": {
"ambiguous_cadence": 2,
"usage_not_monthly": 2
}
},
"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": 2,
"usage_not_monthly": 2
},
"billing_mix": {
"freemium": 2,
"free": 2,
"subscription": 1
},
"free_tier_share": 0.8,
"top_providers": [
{
"agent_id": "agentic_ai_for_lab_automation_",
"name": "Agentic Ai For Lab Automation",
"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 QPillars Agentic AI for Lab Automation."
},
"observed": false
},
{
"agent_id": "aris",
"name": "ARIS (Auto-Research-In-Sleep)",
"price": {
"observed": false,
"billing": "not_found",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public pricing or paid plan details were observed in the supplied homepage context."
},
"observed": false
},
{
"agent_id": "autoresearch",
"name": "AutoResearch",
"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 this open-source GitHub repository."
},
"observed": false
},
{
"agent_id": "bios",
"name": "Bios",
"price": {
"observed": false,
"billing": "not_found",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public subscription or usage plans are listed; the homepage only references estimated compute costs of under $7 or about $8 per design run."
},
"observed": false
},
{
"agent_id": "deepmind",
"name": "Deepmind",
"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": "autonomous-ai-research-lab"
},
"purpose": "full observed price distribution + per-tier medians for this niche"
},
{
"tool": "niche_report",
"arguments": {
"niche": "autonomous-ai-research-lab",
"response_mode": "full"
},
"purpose": "the complete report incl. index series and tier decomposition"
},
{
"tool": "suggest_alternatives",
"arguments": {
"agent_id": "agentic_ai_for_lab_automation_"
},
"purpose": "comparable (optionally cheaper) providers to a named agent"
},
{
"tool": "get_agent_profile",
"arguments": {
"agent_id": "agentic_ai_for_lab_automation_"
},
"purpose": "full profile, integrations and pricing for one provider"
}
]
}
}Full market
4 providers, one sortable view
Dense enough for many listings; progressive disclosure keeps mobile usable.
ProviderTypeFromVs niche medianLiveness
Asterconducts autonomous AI research and experimentation, including optimization of code and LLMs
DreamwalkAn open-source client kit for connecting humans and AI systems to a live research exchange. It supports searching tested idea fragments, submitting ideas for b…
K DenseAI agents for autonomous research execution across science, engineering, healthcare, and finance. Hosted platform with 250+ database access, enterprise deploym…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.