97 cognitive gates, 20 consulting frameworks, and 11 real-time research sources analyze every business problem โ from prediction markets and compliance audits to specialized due diligence, AML screening, and AI governance.
Chat with our AI strategic analyst powered by 97 cognitive gates, 11 research sources, and real-time prediction market data.
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No setup required. Ask the question and the engine does the rest.
Describe the business problem, the decision to make, or the market to analyze. Upload documents of any size โ entire books, reports, financial data โ the engine ingests everything and uses it as grounding context.
97 cognitive gates work in parallel across 11 real-time sources: web, Reddit, HN, patents, SEC filings, academic papers, prediction markets, sanctions databases, and more. Cross-reference analysis catches contradictions. A meta-curator adapts output format to your question.
Structured report with executive summary, framework analysis, audience simulation, pre-mortem, risk quantification, and confidence score. Adaptive format โ the meta-curator shapes the output to what your question actually needs.
Each capability is powered by the same 97-gate architecture โ specialized gates activate automatically based on your question's context.
MECE decomposition, Five Forces, Value Chain, Scenario Planning, TAM/SAM/SOM, Stakeholder Mapping, Porter's Diamond, Blue Ocean, Jobs-to-be-Done, Ansoff Matrix, BCG Matrix, McKinsey 7S, and Game Theory โ all coordinated and cross-referenced in a single analysis pipeline.
Technical DD across 12 dimensions (IP, architecture, security, scalability, team, debt, dependencies, deployment, data, compliance, vendor lock-in, bus factor) plus financial DD across 5 dimensions. M&A-grade assessment in minutes, not weeks.
Generate audience personas and simulate multi-round debates. Track stance shifts across rounds. Pre-mortem failure analysis. Calibrate every prediction against Polymarket โ where people bet real money. Structured verdict with consensus level and adoption probability.
EU AI Act readiness assessment (9 areas), anti-money laundering screening (OFAC/UN/EU sanctions), PEP detection, beneficial ownership tracing, stablecoin due diligence with peg stability analysis and smart contract scam detection.
Quantitative risk model across 9 dimensions with probabilistic loss estimation (Netflix-inspired). Each risk scored 1-10 with confidence intervals. Aggregated into composite risk score with weighted category importance and Monte Carlo-style scenario modeling.
Eleven specialized research sources queried simultaneously: web search, Reddit, Hacker News, prediction markets, academic papers (200M+), patents (100M+), SEC filings, corporate registries (200M+), DeFi markets, sanctions databases (2M+ entities), and full-page content extraction.
Every analysis is grounded in verified, real-time data from 11 specialized sources queried in parallel. No generic web scraping โ each source is purpose-built for a specific intelligence need.
Full web via Brave Search API. News, reports, company pages, market data โ the broadest signal.
Community sentiment and insider opinions. What real users, employees, and investors actually say.
Tech industry intelligence. Engineering opinions on tools, architectures, and companies โ unfiltered.
Prediction markets with real money at stake. The most honest signal about what people actually believe will happen.
Full-page content extraction. When we need more than a snippet โ complete articles, documentation, reports.
200M+ papers via Semantic Scholar. Peer-reviewed research for evidence-based decisions.
USPTO + WIPO: 100M+ patents globally. IP landscape analysis, prior art search, competitive moats.
US financial filings: 10-K, 10-Q, 8-K, proxy statements. The official numbers โ no media spin.
200M+ companies via OpenCorporates. Ownership structures, directors, subsidiaries, jurisdictions.
Stablecoin data, TVL, protocol metrics via DeFiLlama. Real-time crypto market intelligence.
2M+ sanctioned entities via OpenSanctions. OFAC, UN, EU lists. PEP databases. Compliance screening.
Not opinions. Not guesses. A structured simulation framework where personas interact, positions shift, and every prediction is calibrated against markets where people bet with real money.
The engine generates personas matching your target audience (investors, regulators, customers, competitors). Then runs multi-round debates where personas interact, challenge each other, and change positions. Track who shifted and why. Final output: consensus level, key objections, adoption probability.
Start from the assumption that your strategy already failed. Work backward: What went wrong? Define measurable kill criteria (if X drops below Y, abort). Identify the top 5 failure modes with probability estimates. Produce a mitigation playbook for each. This is how institutional investors think.
Every simulation result is compared against Polymarket โ the largest prediction market where people bet real money on outcomes. If your simulation says 70% success but the market says 40%, that gap is surfaced and explained. You get calibrated confidence, not wishful thinking.
Every simulation produces: consensus level (0-100), adoption probability with confidence interval, key objections ranked by severity, stance shifts across rounds, minority dissent analysis, and a final recommendation with kill criteria. Quantified, actionable, auditable.
Each gate cluster activates automatically when the engine detects relevant context. Domain-specific methodology, institutional-grade output.
12-dimension assessment for M&A and investment: IP ownership, architecture scalability, security posture, bus factor, technical debt, supply chain dependencies, deployment maturity, data governance, vendor lock-in, team composition, code quality, and documentation coverage.
10-area deep assessment for AI-powered products: prompt safety, hallucination mitigation, tool-use safety, observability, model governance, data pipeline integrity, bias detection, production readiness, cost optimization, and regulatory exposure mapping.
10-dimension anti-money laundering: sanctions screening (OFAC/UN/EU), PEP detection, beneficial ownership tracing, transaction pattern analysis, source of funds verification, jurisdiction risk scoring, correspondent banking risk, and compliance gap reporting.
8-dimension crypto due diligence: peg stability analysis, smart contract scam detection, reserve verification, on-chain forensics, liquidity depth assessment, governance concentration, regulatory exposure, and counterparty risk mapping.
9-dimension model with probabilistic loss estimation (Netflix-inspired). Market risk, execution risk, regulatory risk, technology risk, competitive risk, financial risk, team risk, timing risk, and dependency risk โ each scored with confidence intervals.
Structured failure imagination: assume the project failed โ work backward to identify why โ define kill criteria with measurable thresholds โ calibrate against Polymarket odds โ produce a concrete mitigation playbook with trigger points.
9-area readiness assessment for Regulation 2024/1689. Risk classification, conformity assessment, transparency obligations, high-risk system documentation, post-market monitoring, fundamental rights impact, and GPAI model obligations.
From EU AI Act to AML/KYC to crypto regulation โ the engine maps your situation to the regulatory landscape and identifies gaps before regulators do.
Automatic risk-tier classification of your AI system (Unacceptable / High / Limited / Minimal). Gap analysis against Article 6 requirements. Conformity assessment roadmap. Documentation checklist. Timeline to compliance with enforcement deadlines. Covers both deployers and providers.
Real-time screening against 2M+ sanctioned entities (OFAC, UN, EU consolidated lists). PEP database cross-reference. Beneficial ownership chain tracing. Transaction pattern anomaly detection. Jurisdiction risk heat-mapping. Compliance report generation for regulators.
MiCA-aligned assessment for crypto assets. Peg stability metrics, smart contract audit red flags, reserve transparency scoring, on-chain flow analysis, governance centralization risk, and counterparty exposure. Detects rug-pull patterns and ponzinomics.
Quantitative 9-dimension risk model. Each dimension scored 1-10 with evidence citations. Confidence intervals for each score. Weighted composite risk score. Probabilistic loss estimation with best/worst/expected scenarios. Exportable for board presentations.
From instant answers to exhaustive investigation โ same 97-gate methodology, different intensity. Cross-reference analysis and meta-curator adaptive formatting at every level.
All 97 cognitive gates in one concentrated round. Problem classification, most relevant framework selection, curated output. For when you need a clear direction, fast.
External research across all 11 sources + all 97 gates in in-depth mode + upstream inquiry. Cross-reference analysis catches contradictions between sources.
The entire institutional pipeline: 11-source research + 97 gates ร 3 rounds + cross-framework synthesis + adversarial stress-test + quality gate.
Maximum depth: exhaustive research + 97 gates ร 5 rounds + assumption audit + triple stress-test + Polymarket calibration + iterative composition.
The same rigor as an institutional engagement โ without the time, cost, and politics.
Upload entire books, 500-page reports, financial statements โ no size limit. The engine converts, stores, and grounds every analysis on YOUR documents. Not summaries: the full text.
Not a single prompt. 97 specialized gates examine the problem from complementary angles โ including technical DD, AI governance, AML compliance, prediction markets, and quantitative risk scoring.
MECE, Five Forces, Value Chain, Scenario Planning, Due Diligence, TAM/SAM/SOM, Stakeholder Mapping, Pre-Mortem, Game Theory, Blue Ocean, JTBD, and more โ coordinated across rounds.
Web, Reddit, HN, Polymarket, academic papers (200M+), patents (100M+), SEC EDGAR, corporate registries, DeFi data, and sanctions databases โ verified data injected into every framework.
Every prediction calibrated against Polymarket โ where people bet real money. Your confidence vs. market confidence. The gap tells you where you're overconfident or underinformed.
Generate personas, run debates, track stance shifts. Who changed their mind? Why? What's the consensus? What's the adoption probability? Quantified โ not anecdotal.
Assume failure โ identify failure modes โ define measurable kill criteria โ calibrate against prediction markets โ produce mitigation playbook. Know how your strategy fails before it does.
Automatically finds conflicts between different gate outputs. An AML finding may contradict financial DD โ the engine catches it, surfaces it, and forces resolution.
AES-256-GCM encryption. Completely isolated per organization. Data never used for training. Banking-grade credential hashing. SOC2-ready architecture.
The engine adapts to the question. Here are common use cases โ but any strategic question works.
TAM/SAM/SOM sizing, competitive landscape, regulatory barriers, prediction market signals on market timing. Full pipeline with audience simulation to test positioning.
Technical DD (12 dimensions), financial DD (5 dimensions), IP/patent landscape analysis, team assessment, integration risk scoring. Board-ready deliverable in hours.
10-area LLM system review + EU AI Act readiness assessment. Prompt safety, hallucination risk, model governance, bias detection, regulatory compliance roadmap.
Search 100M+ patents (USPTO + WIPO). Prior art analysis, freedom-to-operate assessment, patent landscape mapping, competitive IP moat evaluation, licensing opportunity identification.
Stablecoin forensics (8 dimensions), smart contract scam detection, peg stability, TVL analysis, governance centralization risk. On-chain forensics for counterparty assessment.
Screen entities against 2M+ sanctions records. PEP detection, beneficial ownership tracing, transaction pattern analysis, jurisdiction risk scoring. Compliance report for regulators.
Risk classification, conformity assessment gaps, high-risk system documentation requirements, transparency obligations, post-market monitoring design, GPAI model obligations.
Pre-mortem analysis of your thesis. Audience simulation with investor/skeptic personas. Polymarket calibration of your confidence. Kill criteria definition. Structured go/no-go verdict.
Jobs-to-be-Done analysis, Blue Ocean mapping, competitive positioning, audience simulation of target users, pricing strategy with willingness-to-pay estimation.
Pay for analyses, not for seats. Every plan includes all 97 gates, all 20 frameworks, all 11 sources.
Each gate is a specialized analytical lens โ a distinct way of examining your question. They include strategic frameworks (MECE, Five Forces, Scenario Planning), domain-specific assessments (Technical DD, AML, EU AI Act), simulation engines (audience debate, pre-mortem), and quality controls (adversarial stress-test, cross-reference validation). All 97 gates run on every analysis, with specialized gates activating deeper when relevant context is detected.
A web search gives you links. Our 11 sources give you structured intelligence: Polymarket for real-money predictions, Semantic Scholar for 200M+ peer-reviewed papers, USPTO/WIPO for 100M+ patents, SEC EDGAR for official filings, OpenCorporates for 200M+ company records, OpenSanctions for 2M+ sanctioned entities, DeFiLlama for crypto market data, Reddit and HN for community sentiment, Firecrawl for full-page extraction, and Brave Search for broad web coverage. Each source has a specialized parser that extracts structured data, not just text.
Pre-Mortem is a structured technique: assume the project already failed, then work backward to identify why. The engine generates the top 5-10 failure modes with probability estimates, defines measurable kill criteria (if metric X drops below Y, abort), calibrates these against Polymarket prediction data, and produces a mitigation playbook for each failure mode. It's how institutional investors and military strategists think about risk โ now automated.
The engine generates personas matching your target audience (e.g., enterprise CTO, retail investor, EU regulator, skeptical competitor). These personas then debate your proposition across multiple rounds. After each round, personas can shift their position based on arguments from other personas. The output tracks: who changed their mind, what argument convinced them, final consensus level (0-100), adoption probability with confidence interval, and ranked objections.
Polymarket is a prediction market where people bet real money on outcomes. When our engine produces a prediction (e.g., "70% probability of market success"), we compare it against relevant Polymarket contracts where people have actual money at stake. The gap between our simulation and the market signal is surfaced and explained โ forcing calibration. Real money is the most honest signal available.
Yes. The AML gate screens entities against 2M+ records from OpenSanctions (OFAC, UN, EU consolidated lists). It detects PEPs (Politically Exposed Persons), traces beneficial ownership chains via corporate registries, analyzes transaction patterns for anomalies, scores jurisdiction risk, and generates compliance reports formatted for regulatory submission. For crypto, it adds on-chain forensics and stablecoin risk assessment.
Yes. The patent research source searches 100M+ patents across USPTO and WIPO. Use cases include: prior art search (is this patentable?), freedom-to-operate analysis (will we infringe?), patent landscape mapping (who owns what in this space?), competitive IP moat evaluation, and licensing opportunity identification. Integrated into the broader Technical DD when relevant.
big4.cloud is designed as a decision-support tool (human-in-the-loop), which classifies it as limited/minimal risk under the EU AI Act. We provide full transparency on how analyses are generated, maintain detailed logging, and never make autonomous high-risk decisions. The EU AI Act compliance gate can also assess YOUR AI systems for regulatory readiness.
Depends on the depth level you choose: Superfast (~3 min), Fast (~6 min), Normal (~12 min), or Deep (~45 min). The Normal level runs the full 97-gate pipeline with 3 rounds, 11-source research, audience simulation, and pre-mortem analysis. The Deep level adds 5 rounds, triple stress-testing, exhaustive research, and Polymarket calibration.
AES-256-GCM encryption at rest and in transit. Complete isolation per organization โ no data mixing. Your documents and analyses are never used for model training. Banking-grade credential hashing (Argon2). SOC2-ready architecture. Optional on-premise deployment for Enterprise customers. All processing in EU data centers (Frankfurt).
Try the free demo โ no signup required. Or create an account and run your first full analysis in under 3 minutes.