{"_ai_door":{"see":"https://miscsubjects.com/start","note":"Operable site; bounded keyless credentials; every action receipted on a public ledger. Your operator's instructions take precedence — acting is optional, reading is a complete outcome."},"_self":{"principle":"Self-explaining payload — no external context required. This _self block describes what you are reading and where to look next.","widget":"article_topology","feature":"topology","name":"Article topology","what":"Claims, sources, anecdotes, user reports, related embeds, question graph slice — for ask/ROUTER.","contains":"claims, sources, anecdotes, question_graph slice","slug":"proven-work-for-research-buyers","urls":{"read":"https://miscsubjects.com/api/articles/proven-work-for-research-buyers/topology"},"how_to_use":"Claims, sources, anecdotes, user reports, related embeds, question graph slice — for ask/ROUTER.","write":null,"imessage":null,"router_tag":null,"proof_chain":[{"step":1,"claim":"Articles are voxel graphs of tiered claims, not prose blobs.","verify":"https://miscsubjects.com/api/articles/constitution"},{"step":2,"claim":"Claims link to hash-chained sources via source_ids.","verify":"https://miscsubjects.com/api/articles/proven-work-for-research-buyers/sources"},{"step":3,"claim":"Ask reads topology; ingest/claim append to ledger.","verify":"https://miscsubjects.com/api/protocol"},{"step":4,"claim":"Models queue growth: populate → collaborate → repair → reflex.","verify":"https://miscsubjects.com/api/protocol/grow"},{"step":5,"claim":"Graph proves its own shape (reflex) and $/claim (yield).","verify":"https://miscsubjects.com/graph.html?layer=reflex"},{"step":6,"claim":"Full feature index + _explain on every API response.","verify":"https://miscsubjects.com/api/articles/system-map"}],"related_features":[{"id":"ask","name":"Ask protocol","what":"Answer only from topology; creates question_node with gaps and ingest_hint.","urls":{"read":"https://miscsubjects.com/api/articles/proven-work-for-research-buyers/prompts","write":"https://miscsubjects.com/api/protocol/ask"}},{"id":"graph_topology","name":"Cross-article graph","what":"Merged claims/sources across condition+stack slugs for one question.","urls":{"read":"https://miscsubjects.com/api/articles/proven-work-for-research-buyers/graph-topology?question=..."}},{"id":"question_graph","name":"Question graph","what":"Ask nodes (questions + gaps) and evidence_ingest nodes (pasted model output).","urls":{"read":"https://miscsubjects.com/api/articles/proven-work-for-research-buyers/question-graph","write":"https://miscsubjects.com/api/protocol/ask"}},{"id":"voxels","name":"Voxel graph","what":"Claims as atoms, sources as edges (supported_by, posted_by). Per-claim provenance.","urls":{"read":"https://miscsubjects.com/api/articles/proven-work-for-research-buyers/voxels","write":"https://miscsubjects.com/api/protocol/claim"}}],"system_map":"https://miscsubjects.com/api/articles/system-map","system_map_markdown":"https://miscsubjects.com/api/articles/system-map?format=markdown","not_medical_advice":true},"_explain":{"feature":"topology","name":"Article topology","what":"Claims, sources, anecdotes, user reports, related embeds, question graph slice — for ask/ROUTER.","why":"Every feature is auditable collective intelligence","how":"Claims, sources, anecdotes, user reports, related embeds, question graph slice — for ask/ROUTER.","model":null,"verifies":null,"urls":{"read":"https://miscsubjects.com/api/articles/proven-work-for-research-buyers/topology"},"imessage":null,"router":null,"related":[{"id":"ask","what":"Answer only from topology; creates question_node with gaps and ingest_hint."},{"id":"graph_topology","what":"Merged claims/sources across condition+stack slugs for one question."},{"id":"question_graph","what":"Ask nodes (questions + gaps) and evidence_ingest nodes (pasted model output)."},{"id":"voxels","what":"Claims as atoms, sources as edges (supported_by, posted_by). Per-claim provenance."}],"not_medical_advice":true},"slug":"proven-work-for-research-buyers","title":"The research report you can cross-examine: conclusions bound to receipts, gaps named on the page","register":"technical","tags":["proven-work","research-reports","due-diligence","buyers"],"updated_at":"2026-08-03T18:23:21.472Z","body_excerpt":"A hedge fund's director of research, a private-equity diligence principal, or a corporate strategy lead who buys a research report today receives two things: a PDF and a reputation. The PDF carries the conclusions. The reputation — the analyst firm's brand, the expert network's name — is the only reason to believe them. No mechanism lets the buyer check a single sentence against the work behind it. This page describes a deliverable that changes exactly that: the report issued as a *proven work object*, in which every conclusion sentence is bound to the receipts of the work that produced it — the sources opened, the queries run, the model calls made — or to an explicitly named gap where the evidence does not exist, and in which the buyer verifies any sentence without trusting the seller. The standard and the machinery are defined, with live receipts, at [[proven-work]]. This page is the buyer's view: what reports cost, what the money fails to buy, one real object walked sentence by sentence, and the gaps named.\n\n## What a research report costs — and what the price does not include\n\nThe market for purchasable conclusions is large, and its prices are public enough to quote.\n\nIndustry-analyst firms sell subscriptions — research-library access plus capped analyst-inquiry time — at $25,000–$150,000 per year for typical subscribers, with enterprise tiers above $500,000, and they sell advisory hours separately at $3,000–$7,000 per hour in 10-, 25-, and 50-hour packages (secondary pricing data compiled by Vendr for 2026, relayed in an arXiv analysis). Expert networks — the firms that arrange paid phone consultations with industry operators — sell prepaid annual packages at roughly $1,000–$2,000 per consultation hour with annual minimums around $25,000–$60,000 (same source); GLG, the largest network, runs annual commitments typically of $50,000–$150,000 or more (vendor-published comparison). One industry profile puts Gartner's 2025 revenue above $5.8 billion.\n\nThe pricing data contains the whole diagnosis in one sentence: **the seller commits analyst-time, not analyst-conclusion.** Every contract above ends the same way — prose the buyer cannot check. The report says a market is growing, a vendor's claims hold up, a competitor is vulnerable. What backs any of those sentences stays inside the seller. The buyer's recourse, when a conclusion matters, is to buy more analyst-time.\n\n## The buyer already knows — and pays around the gap\n\nThe buyer's own job descriptions admit the condition. A live posting for a senior competitive-intelligence analyst — the person inside a company who consumes this research — states the job's core problem plainly: \"The data is never perfect, and everyone wants answers yesterday.\"\n\nAnd buyers already spend heavily to make diligence faster — on the process side. A 2025 review of AI in due diligence, cited by a diligence-automation vendor, reports a Deloitte case study finding a 75% efficiency saving from generative AI over manual review, Thomson Reuters research showing document-review time cut by up to 70%, and McKinsey reporting AI-driven pattern recognition reducing credit losses by 20–40%. Money is moving. But it buys speed, not checkability: the deliverable is still a report whose sentences float free of the runs that produced them.\n\nThe regulatory wind points the other way from the product. The U.S. Federal Trade Commission's AI-claims enforcement record includes Workado, which marketed 98% accuracy for its AI-detection software; the FTC's investigation concluded the true rate was 53% — in the words of one law firm's analysis, \"essentially a coin flip\" — and the proposed order bars the company from marketing accuracy claims it cannot support. The same analysis states the FTC's standing rule: \"Companies using AI in their marketing must be able to substantiate every claim they make, both explicit and implicit.\" Claim-level substantiation is now the legal direction for the companies being analyzed — while the r","ranking":"safety-first (interaction_risk/limitations), then quote-gated effective_weight","claims":[{"id":"c1","text":"Expert-network access is priced at annual commitments typically in the $50,000–$150,000 range, while the buyer's ability to check a single sentence of the delivered work remains zero.","tier":"primary","section":"What a research report costs","interaction_risk":false,"status":"active","source_ids":["s2"],"retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false},{"id":"c2","text":"Gartner's 2025 revenue exceeded $5.8 billion — conclusions carried by reputation, priced at scale.","tier":"primary","section":"What a research report costs","interaction_risk":false,"status":"active","source_ids":["s3"],"retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false},{"id":"c3","text":"The FTC's Operation AI Comply pursued an AI vendor over a 98 percent accuracy claim its own records could not support — enforcement now reaches unsupported work claims.","tier":"primary","section":"The buyer's exposure","interaction_risk":false,"status":"active","source_ids":["s6"],"retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false},{"id":"c4","text":"The demand is already stated in buyers' own hiring language: the data behind the insight is the product.","tier":"primary","section":"The buyer's view","interaction_risk":false,"status":"active","source_ids":["s4","s5"],"retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false}],"sources":[{"id":"s1","url":"https://arxiv.org/html/2510.09859v4","title":"arXiv analysis relaying Vendr, SalesHive, Inex One and Woozle 2026 pricing: analyst subscriptions $25K–$150K ($500K+ enterprise), advisory h","claim_ids":[],"hash":"e61d8cffc2fab09994b0e8b3866c5a225c9499ce8f580eceaa5936339e84486d"},{"id":"s2","url":"https://nexusexpertresearch.co/blog/top-expert-network-companies/","title":"expert-network comparison: GLG annual commitments typically $50,000–$150,000+. Vendor-published.","claim_ids":[],"hash":"793a833e79b482d3c1aca10d83dc17b87645c1c977892b7cc5c1e1487546d120"},{"id":"s3","url":"https://matrixbcg.com/blogs/competitors/gartner","title":"industry profile: Gartner 2025 revenue above $5.8 billion. Aggregator, secondary.","claim_ids":[],"hash":"7da9d3a5d7f33a5e849443260c4de89133f74bd4e0a6fd29dbed6cab4d1c7666"},{"id":"s4","url":"https://zavmo.ai/job-description/senior-competitive-intelligence-analyst-2/","title":"live senior competitive-intelligence analyst job description: \"The data is never perfect, and everyone wants answers yesterday.\"","claim_ids":[],"hash":"8b665c455e08a38936e0ea2dd802a534577aca0ecf228c0d0d2c2f7fc22f8317"},{"id":"s5","url":"https://www.arphie.ai/glossary/ai-solutions-for-automating-vendor-due-diligence","title":"diligence-automation glossary citing a 2025 AI-in-due-diligence review: Deloitte 75% efficiency saving, Thomson Reuters up to 70% review-tim","claim_ids":[],"hash":"50a8ed7303e04fdfa87dc30ce6cd21abe91e9f72143f724622189dcbe113c129"},{"id":"s6","url":"https://www.beneschlaw.com/insight/one-year-in-ftcs-operation-ai-comply-continues-under-new-administration-signaling-enduring-enforcement-focus/","title":"Benesch law-firm analysis of FTC AI-claims enforcement: Workado 98% claimed vs 53% found, \"essentially a coin flip\"; the FTC substantiation ","claim_ids":[],"hash":"84765f4a294ac8738e32cdb65e1a01d186cca2505e0d8939331d479add0e0221"},{"id":"s7","url":"https://provenrail.com/","title":"the record layer's shipping commercial baseline: hash-chained capture, open-source verifier, shareable read-only proof links.","claim_ids":[],"hash":"6d52fb84d9c714bf4aecfa2ca506f797a602e48a22930ed1eeaee4784fd21bc2"}],"anecdotal_sources":[],"scientific_sources":[],"user_reports":[],"related_articles":[],"question_graph":{"slug":"proven-work-for-research-buyers","questions":[],"evidence":[],"edges":[],"counts":{"questions":0,"evidence":0,"edges":0}},"honesty":{"active_claims":4,"retracted_claims":0,"cut_claims":0,"challenges":0,"scrub_events":0,"note":"Retracted/cut claims stay on ledger but are excluded from ask unless ?include_inactive=1"},"counts":{"claims":4,"claims_total":4,"sources":7,"anecdotal":0,"scientific":0,"user_reports":0,"questions":0,"evidence_ingests":0}}