big4.cloud is a structured reasoning engine that applies over 90 cognitive gates and 13 consulting frameworks to any business problem. Not a chatbot. A complete consulting process — with automatic research, adversarial stress-testing, cryptographic source traceability, and reproducibility guarantees.
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 format and size — 500-page reports, financial statements, pitch decks, entire books — the engine ingests everything and uses it as the foundation of the analysis.
Over 90 specialized cognitive gates work in parallel: they decompose the problem, gather external data from multiple sources (Reddit, Hacker News, Brave Web, Polymarket, Firecrawl), apply 13 strategic frameworks, synthesize where they converge and contradict, and stress-test every conclusion with a mandatory adversarial red-team.
Structured report in 10 sections: executive summary, per-framework analysis, cross-framework synthesis, numbered assumption register, adversarial stress-test, composite confidence score, operational recommendations. Every source is cryptographically verifiable. Every conclusion is traceable.
big4.cloud works via MCP (Model Context Protocol). Connect it to Claude, Cursor, or any MCP-compatible client with one config line.
Sign up free at big4.cloud/register. You'll get an API key and 3 free analyses immediately.
Add this to your MCP config (Claude Desktop, Cursor, Kiro, or any MCP client):
Ask any strategic question. The engine activates automatically — 62 tools ready, zero configuration.
{
"mcpServers": {
"big4cloud": {
"url": "https://big4.cloud/api/v1/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_KEY"
}
}
}
}Download skill.md from GitHub and paste it into your AI's custom instructions (Claude Desktop → Settings → Custom Instructions; Cursor → .cursorrules). The skill adds automatic triggers in 5 languages.
Full skill source, documentation, and MCP tool reference. Star it if you find it useful.
That's it. No SDK, no binary, no Docker, no dependencies. Just a URL and a key.
No other product on the market combines structured multi-perspective reasoning with cryptographic audit trails, source verification, and reproducibility guarantees. This is not a marketing claim — it's a technical description of what the system does.
| Capability | big4.cloud | ChatGPT / Claude | Perplexity | Traditional Consulting | BI Tools | AI Agents |
|---|---|---|---|---|---|---|
| Multi-gate structured reasoning (90+ perspectives) | ✓ | ✗ single response | ✗ | ✗ manual, not scalable | ✗ | ✗ |
| Mandatory adversarial red-team | ✓ automatic | ✗ | ✗ | ✓ but manual & costly | ✗ | ✗ |
| Cryptographic source verification (SHA-256 + Merkle root) | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Reproducibility guarantee (consistency score + contradiction detection) | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Complete audit trail (append-only, hash-chained) | ✓ | ✗ | ✗ | Partial (documents) | ✗ | ✗ |
| What-if branching with selective re-execution | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Decision genealogy with drift monitoring | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ |
| SOX 404 evidence generation | ✓ | ✗ | ✗ | ✓ but €100k+ | ✗ | ✗ |
| 13 coordinated consulting frameworks | ✓ | ✗ | ✗ | ✓ same frameworks, months of work | ✗ | ✗ |
| Delivery time | Minutes | Seconds (but superficial) | Seconds (search only) | Weeks/months | N/A | Variable |
| Cost per analysis | From €0 | Generic subscription | Generic subscription | €100k+ per engagement | License + analyst | Custom setup |
90+ specialized cognitive perspectives, not a single LLM response. Each gate has a specific discipline. The output is the product of systematic convergence and contradiction.
Every analysis undergoes stress-testing before delivery. Not optional: it's part of the process.
Every source has an individual SHA-256 hash. A Merkle root links the entire set to the governance chain. Any tampering is automatically detected.
The system tracks directional consistency across successive executions. Detects monotonic refinements (legitimate), flags contradictions (defects), classifies every delta.
Append-only blackboard. Hash-chained governance log. Nothing is ever deleted.
Fork a decision with modified assumptions. The system selectively re-executes only the affected gates and produces a structured diff.
Every decision is a node in a graph. The system monitors when foundational assumptions degrade and calculates cascading impact.
For regulated environments. The system automatically generates the evidence package for internal controls.
From instant answers to exhaustive investigation — same methodology, different intensity.
All 90+ cognitive gates in one concentrated round. Problem classification, most relevant framework selection, curated output. For when you need a clear direction, fast.
External research + all gates in in-depth mode + upstream inquiry. For daily decisions that deserve rigor, not just intuition.
The entire institutional pipeline: research + 90+ gates × 3 rounds + cross-framework synthesis + adversarial + quality gate. The gold standard for important strategic decisions.
Maximum depth: exhaustive research + 90+ gates × 5 rounds + assumption audit + triple stress-test + iterative composition. For the decisions that define the company's future.
The same rigor as an institutional engagement — without the time, cost, and politics.
Upload entire books, 500-page reports, financial statements — no size limit. The engine converts, stores, and grounds every analysis on YOUR documents. Not summaries: the full text.
OCR for scanned documents — coming next updateNot a single LLM that "thinks." Over 90 specialized cognitive gates — each with a discipline, an angle, a specific function — examining the problem from complementary perspectives. They converge where they agree, flag where they contradict, highlight blind spots.
MECE, Issue Trees, Pyramid Principle, Five Forces, Value Chain, Scenario Planning, Stakeholder Mapping, Due Diligence, Market Sizing (TAM/SAM/SOM), Business Case, Pareto, Adversarial Red Team, Assumption Audit. Applied in coordination, not isolation.
The engine doesn't apply frameworks in silos. After execution, a synthesis phase identifies where frameworks converge (strong signal), where they contradict (risk area), and where they leave blind spots (gaps to investigate).
Before every analysis: Brave Web Search, Reddit discussions, Hacker News technical perspective, Polymarket prediction markets, Firecrawl full-page crawling. Real data injected into every framework for grounded conclusions.
Every analysis undergoes red-team: a specialized panel attacks conclusions, verifies assumptions, identifies weak points, and finds scenarios where the strategy would fail. Not optional — part of the pipeline.
Every deliverable is evaluated on 8 institutional quality criteria, each scored 0-100. The report is not delivered until it passes the minimum rigor threshold.
Transparent formula: framework convergence (40%) + data quality and completeness (30%) + assumption resilience (30%). Not an arbitrary number — a calculated indicator of how much to trust the result.
Every assumption is: numbered and identifiable, classified by confidence level, traced to its supporting source, and monitorable over time for drift.
Three different AI models (DeepSeek, Gemini, Qwen) analyze from three specialized angles: strategic, critical/risks, and operational. An Assembler fuses without repetition for deeper, multi-dimensional output.
Institutional-level audit pipeline: fact-check, audience simulation (8 personas), enhancement, confidence delta, kill criteria, contradiction map, time-travel scenarios, drift monitor, scenario stress, final synthesis.
Append-only blackboard: every contribution recorded. Trace the logical path from input to conclusion. Hash-chained governance log. Cryptographically verifiable reference set.
A 10-phase pipeline that verifies, stress-tests, and enriches any analysis — with kill criteria, audience simulation, and time-travel scenarios.
| Phase | Name | What it does |
|---|---|---|
| 1 | Fact Check | Verifies every claim against Brave, Reddit, Polymarket, Hacker News |
| 2 | Audience Simulation | 8 diverse personas react to the deliverable (investors, clients, critics, operators) |
| 3 | Enhancement | Re-analysis incorporating fact-check and audience feedback |
| 4 | Confidence Delta | Shows exactly how much confidence improved (before vs. after) |
| 5 | Kill Criteria | Automatically generates the conditions to ABANDON the strategy |
| 6 | Contradiction Map | Shows where gates, fact-checker, and audience disagree |
| 7 | Time-Travel | "What if you had decided 3 months ago? What if you wait 3 months?" |
| 8 | Drift Monitor | Registers assumptions for future monitoring |
| 9 | Scenario Stress | Parametric variations on key assumptions |
| 10 | Final Synthesis | Enriched deliverable with all validations incorporated |
Against multiple real sources — not just the LLM's training data.
When to stop investing in this direction. Automatically generated conditions.
What would have happened earlier, what happens if you wait. Temporal sensitivity analysis.
Quantitative measurement of improvement — before and after the audit.
Where perspectives diverge unresolved — the areas that need attention.
Pre-test your pitch before the real presentation. 8 personas with different backgrounds, seniority, and attitudes.
Two capabilities that don't exist in any other analysis system on the market.
Every source gets a unique digital fingerprint. Any post-delivery alteration is detectable immediately.
Links the entire source set to the governance chain. Binary tree ordered by source_id. Tamper-evident by construction.
If anyone alters sources after delivery, the hash doesn't match and the system flags it automatically.
Measures how stable conclusions are between runs. Tracks monotonic refinement — enrichment is legitimate, contradictions are not.
Every claim classified: STABLE (unchanged), REFINEMENT (same direction, stronger), ADDITION (new finding), CONTRADICTION (load-bearing claim inverts), DROP (present before, absent after).
Deeper runs must not contradict shallower runs. Contradictions are critical events, not noise. Formula: (stable + refinement) / total × 100 − (drops × 0.5).
Also included: URL deduplication + canonicalization (no duplicates, no ambiguity), fetch failures shown (honesty: what was attempted but unavailable), references.json machine-readable manifest for automatic integration. Every blackboard entry with external provenance maps obligatorily to a SourceRecord. No exceptions.
Structured analysis across 5 dimensions (commercial, financial, operational, legal, strategic) with traffic-light rating for each risk. Complete assumption audit with source for every assumption.
Five Forces + Value Chain + positioning + white space analysis. Not just where you are — where the market is heading and where there's room.
Dual top-down + bottom-up methodology with automatic cross-check. TAM, SAM, SOM with assumptions explicit, numbered, and verifiable.
2×2 scenario planning, stakeholder mapping, structured business case with sensitivity analysis on key variables.
M&A, product launch, geographic expansion, strategic pivot, partnership — the engine examines from every angle before the decision. What-if branching to test alternative scenarios.
Same methodological rigor as a big-firm engagement — results in minutes, not weeks. Accessible to startups, SMEs, and enterprises.
Immutable audit trail, SOX 404 evidence generation, 4-eyes approval workflow, automatic decision classification. For regulated environments.
Knowledge graph that grows over time. Drift monitoring on assumptions. Cross-pollination between teams. The system becomes smarter with every use.
Built for regulated environments and complex organizations.
Every decision becomes a node in a persistent graph. The system tracks relationships (caused_by, supersedes, contradicts), extracts load-bearing assumptions via a 3-stage pipeline (explicit, premise, LLM), and monitors degradation with temporal decay. When an assumption collapses, impact cascade (BFS, max 100 nodes) computes which downstream decisions are at risk. Automatic clustering: when 3+ assumptions in the same category signal drift, the system generates a cluster alert.
Decision-level access control with 5-level hierarchy (view < view_full < comment < approve < admin). Approval workflow with 4-eyes principle: no critical decision ships without independent review. Immutable audit log with SHA-256 hash chain — each entry linked to the previous, any tampering detected. Automatic classification (routine/significant/critical/board_level). Automatic SOX Section 404 evidence generation. Per-tenant governance policy with minimum 365-day retention.
Fork a decision with 1-5 modified assumptions. The system analyzes the blackboard dependency DAG, identifies affected gates via seed detection and BFS, and re-executes only those (selective execution). Produces a structured diff (gate-by-gate + LLM recommendation comparison) and computes sensitivity: change_magnitude × recommendation_weight. Each scenario is a branch in a navigable tree.
Per-team namespaces with total isolation. Each team extracts insights from their decisions (LLM extraction) and can share them selectively via outbound/inbound policies. Subscribed teams receive automatic cross-pollination: relevant insights injected as synthetic blackboard entries in new decisions. Cross-namespace semantic search (cosine similarity) respecting isolation boundaries.
Real compliance with cryptographically verifiable sources on the final document. Every deliverable includes a structured reference set with SHA-256 hashes for each source — linked to the governance chain via binary Merkle root (ordered by source_id). Any source tampering is automatically detected. Append-only store with SQL triggers (BEFORE UPDATE/DELETE). Deduplication by canonical URL (full normalization: lowercase, no tracking params, no fragments, sorted query) and by content hash (alias). Fetch failures documented for honesty. The system also tracks directional consistency across successive analyses: detects monotonic refinements, flags contradictions, classifies each delta, and computes a stability score with transparent formula. Two MCP tools (references_get, genealogy_consistency) make this accessible via API.
Each tier increases depth, not methodology.
No. big4.cloud is a structured reasoning engine. It takes a problem, decomposes it systematically through 90+ cognitive perspectives and 13 frameworks, and produces a structured deliverable in 10 sections. The difference between asking a friend for an opinion vs. commissioning a study from an institutional consulting firm.
A generic LLM produces a single response from a single perspective. big4.cloud orchestrates 90+ specialized gates that work in parallel, contradict each other, stress-test each other, synthesize where they converge and diverge, and converge toward an output subjected to systematic adversarial scrutiny. Plus: cryptographic source traceability, consistency score between runs, numbered assumption audit. It's the difference between an opinion and a due diligence process.
Perplexity does research + synthesis: it searches sources and summarizes. big4.cloud does structured reasoning: it applies 13 consulting frameworks, 90+ cognitive perspectives, adversarial stress-test, cross-framework synthesis, and produces a deliverable with audit trail, confidence score, and cryptographic source verification. Perplexity answers questions. big4.cloud produces strategic analyses.
Same methodological rigor, same frameworks, same structure — but executed by a software engine, not a team of 5 consultants for 6 weeks. The result is comparable in structure and depth; the cost is orders of magnitude lower because execution is automated. The methodology is not.
Every source used in the analysis receives an individual SHA-256 hash. The complete source set produces a Merkle root linked to the governance chain. If anyone alters a source after delivery, the hash doesn't match and tampering is automatically detected. The system also shows fetch failures — sources attempted but unavailable — for honesty.
The system tracks directional consistency across successive executions. If you analyze the same topic twice, the engine classifies every difference: STABLE (unchanged), REFINEMENT (enriched in same direction), ADDITION (new finding), CONTRADICTION (load-bearing claim inverts), DROP (claim disappeared). Deeper runs must not contradict shallower runs. Contradictions are critical events, not noise.
Three different AI models (DeepSeek, Gemini, Qwen) analyze the same blackboard from three specialized perspectives (strategic, critical/risks, operational). An Assembler fuses without repetition. Costs 5 credits. Produces deeper output than standard mode. Recommended for high-impact decisions.
A 10-phase pipeline (15 credits) that verifies, enriches, and stress-tests any analysis: fact-check against multiple sources, audience simulation with 8 personas, automatic kill criteria, time-travel scenarios, contradiction map, measurable confidence delta.
Every organization has completely isolated data (multi-tenant). We don't use user content for training. The blackboard is append-only (we never delete). Credentials are hashed with banking-grade standards. The audit log is hash-chained and verifiable.
Yes. big4.cloud exposes 62+ tools via MCP (Model Context Protocol) compatible with Claude Desktop, Cursor, and any MCP client. REST API with JWT or API key. Chat via Telegram, Slack, Discord, Matrix. Document upload of any format and size.
Always. Every analysis produces a complete blackboard where you see each gate's contribution, data provenance, the logical path from input to conclusion, and the reference set with cryptographic hashes. No black box.
Yes — with no size limit. Entire books, 500-page reports, financial statements, pitch decks, market studies. The engine converts them to searchable text, stores them in your persistent knowledge base, and uses them to ground every future analysis. No truncation, no unsolicited summaries. OCR for scanned documents coming soon.
Anyone making complex strategic decisions: CEOs, founders, CFOs, heads of strategy, consultants, investors, board members. From the analyst who needs to prepare a report in 2 hours to the board deciding an acquisition.
60 seconds: 1) Register free at big4.cloud to get your API key. 2) Add the MCP server URL (https://big4.cloud/api/v1/mcp) with your key to Claude Desktop, Cursor, or any MCP client. 3) Optionally, download skill.md from github.com/al3max/big4skill and paste it into your AI's custom instructions for automatic triggers in 5 languages. That's it — no binary, no Docker, no dependencies.
Free plan: 3 analyses/month, no credit card. Pro plan: €500/month for regular analyses. Enterprise: custom pricing for teams needing governance, compliance, and maximum depth.