Commercial Solutions for Industries & Enterprises
GoDataX Human 7 applies the platform’s measurement discipline to groups and individuals, Free solution for the psychology and philosophy scientific community that combining psychometrics, cardiac coherence, adaptability, metaphysics, and wellbeing. The other Commercial Solutions, The GoDataX Cognitive Trust Platform H7 (CTP H7) is offered to organizations by TwoData FZCO under “Other Solutions,” covering governed data, quality, semantics, AI agents, monetization, and blockchain-backed trust at scale.
GoDataX CTP H7 — Architecture & Components
GoDataX CTP H7 unifies data quality, governance, knowledge, and explainable AI into a single cognitive operating system where rules, semantics, and context are executable, auditable, and reusable by design, including how people think, feel, and grow. It delivers enterprise-grade governance, quality, and human-centric intelligence with blockchain-backed trust.
A Unified Knowledge Graph for AI and Analytics
GoDataX Metadata consolidates technical, governance, and SPU metadata into a single enterprise Knowledge Graph. Instead of fragmented catalogs and static documentation, metadata becomes a living, connected model of reality that statistical models, LLMs, and agents can navigate. The result is trustworthy AI, context-aware analytics, and real-time governance with explicit relationships across assets, pipelines, controls, risks, metrics, domains, and business intent.
Enterprise Knowledge Graph foundation
Connect assets, pipelines, lineage, domains, metrics, controls, risks and evidence as nodes and relationships, making meaning and dependencies queryable at scale.
AI-ready contextual metadata
LLMs and models consume governed context (definitions, constraints, policies, criticality) instead of guessing from raw tables, reducing hallucination and improving accuracy.
Executable governance (not documentation)
Policies, checks, SLAs, evidence, issues and remediation become active graph entities, enabling continuous, auditable governance with clear accountability.
Real-time impact analysis
Instantly propagate changes across jobs, metrics, dashboards, models, risks and use cases, preventing incidents and reducing rework.
Better economics for data & AI
Cut operational overhead (manual analysis, audit effort, rework), reduce production failures, and accelerate AI adoption with trusted evidence, improving ROI across analytics and automation programs.
Built for agents and automation
Enable autonomous workflows and AI agents to select the right assets, apply the right policies, prioritize remediation, and operate safely within governed constraints.
Governance at Business Speed
GoDataX Governance transforms traditional data governance from static documents into an executable, metadata-driven control system. Policies, rules, ownership, and constraints are enforced directly inside data pipelines, analytics workflows, and XAI execution with full traceability and auditability. Governance becomes continuous, scalable, and aligned with real business operations.
- Executable governance controls: policies, rules, approvals, and constraints enforced directly in pipelines and XAI workflows.
- End-to-end traceability: full lineage across data, models, decisions, and XAI outcomes with auditable evidence.
- Enterprise compliance by design: built-in support for LGPD, ISO, BCBS, SOX… and internal risk policies.
What makes GoDataX Assurance different?
GoDataX Assurance operationalizes Data Quality as a continuous, auditable execution layer inside your pipelines. Instead of running “one-off” checks, it turns rules, constraints, metrics, and SLAs into repeatable controls, generating evidence, traceability, and actionable signals for teams and stakeholders.
Executable quality rules
Define and run checks continuously (not manually), aligned with pipeline stages and critical datasets.
Automated metrics & thresholds
Track DQ indicators over time (completeness, validity, consistency, etc.) with thresholds and alerts.
Constraints at pipeline level
Enforce constraints where data is produced/consumed, reducing silent failures and downstream impact.
Auditable evidence & lineage
Produce execution evidence (runs, results, errors) plus technical metadata and end-to-end lineage.
SLA monitoring & breach detection
Monitor SLAs continuously and detect breaches early, with clear accountability and operational follow-up.
Native workflow integration (n8n / pipelines)
Connect quality execution to workflows for notifications, approvals, remediation tasks, and automation.
GoDataX SPU (Semantic Processing Unit)
GoDataX SPU is the semantic and cognitive core that turns governed data into trusted intelligence. It transforms technical metadata + business knowledge into semantic assets (domains, glossary, narratives, ontology), persists them as an enterprise Knowledge Graph, and exposes XAI-ready Semantic APIs so LLMs and RAG consume meaning, context, and constraints, not raw tables. The SPU also provides an algorithmic asset registry (on-chain ready for private blockchain) to guarantee provenance, integrity, and end-to-end decision traceability.
XAI-ready semantic layer
Semantic APIs for RAG/LLMs with context, policies, and constraints embedded.
Enterprise Knowledge Graph
Domains, glossary, metrics, lineage and relationships, queryable and reusable at scale.
On-chain provenance
Algorithmic registry + proofs for assets, versions, and executions on private blockchain.
Explainable decisions
Governed KG + evidence trail enables explainable AI and audit-ready outcomes.
GoDataX Enterprise RAG-XAI Agents
GoDataX Agents are enterprise-grade XAI workflows orchestrated by n8n, grounded in trusted data and enforced by governance. Instead of “prompt-only” automation, the agent executes with quality evidence, policies & constraints, SPU semantics, knowledge graph context, and blockchain proofs, enabling traceable decisions, compliant operations, and reliable outcomes across regulated environments.
Policy-driven RAG
Retrieval and actions are constrained by Governance rules (access, purpose, domain, sensitivity) not just prompts.
End-to-end traceability
Full lineage from prompt → data → rule → decision, with evidence, approvals, and audit-ready logs.
Trusted context (SPU + KG)
SPU semantic layer + Knowledge Graph reduce ambiguity and hallucinations with consistent business concepts.
Compliance & security
Multi-tenant orchestration with governance controls and optional blockchain proofs for tamper-evident trails.
Moderation Integration
When enabled in GoDataX CTP H7, content classification and control are performed in real time, allowing the process to be blocked or allowed based on policy rules.
Moderation and classification by categories
Harassment, Harassment/Threatening, Hate, Hate/Threatening, Illicit, Illicit/Violent, Self-harm, Self-harm/Intent, Self-harm/Instructions, Sexual, Sexual/Minors, Violence.
Enterprise audit trail & evidence
Records decision evidence (category, score, applied action, policy version) to support compliance. Optionally integrates with immutable trails (e.g., blockchain proofs) for tamper-evident accountability.
Commercial outcomes
Reduces reputational and legal risk, accelerates AI channel go-live, and standardizes content governance at scale, with clear SLAs and quality metrics by category and business unit.
GoDataX Monetization
GoDataX Monetization converts trusted data into scalable business value by generating model-driven outputs (forecasts, anomalies, segments, scores and deep-learning signals) and exposing results through AI Chat or APIs ready to embed into pricing, growth, risk, and operational decisions.
Monetize model outputs
Create data products from forecasts, segments, and scores packaged as services, dashboards, or APIs.
Operationalize decisions
Embed results into workflows (pricing, churn, fraud, demand, inventory) with measurable ROI.
Chat IA + API ready
Deliver insights via governed Chat for users and via API/Webhook for systems and apps.
Enterprise governance
Combine quality + governance + evidence so models are trusted, explainable, and audit-ready.
Model Portfolio (Current + Next Options)
1️⃣ Statistical Forecast (baseline now — Active)
- Outputs: forecasts, trends, seasonality, confidence bands.
- Benefits: demand planning, budget accuracy, proactive operations.
- Monetization: publish monthly/weekly forecast feeds via API and executive dashboards.
2️⃣ Anomaly Detection (forecast residuals)
- Outputs: anomalies, root-cause candidates, alert severity.
- Benefits: detect fraud/leakage, data issues, operational incidents early.
- Monetization: alerting-as-a-service + SLA-driven incident triggers via webhook.
3️⃣ Clustering (behavior segmentation)
- Outputs: segments, profiles, drivers, transition patterns.
- Benefits: targeted offers, differentiated pricing, portfolio optimization.
- Monetization: segment-based products (premium insights, market intelligence packs).
4️⃣ Supervised Models (classification / regression)
- Outputs: propensity scores, risk scores, value predictions, ranking.
- Benefits: churn prevention, upsell, credit/risk decisions, SLA optimization.
- Monetization: scoring endpoints (real-time) consumed by CRM/ERP/apps via API.
5️⃣ Deep Learning (comparative / advanced patterns)
- Outputs: embeddings, complex pattern detection, multivariate signals.
- Benefits: higher accuracy on nonlinear behavior, complex interactions, edge cases.
- Monetization: premium models (higher-value tier) + explainable summaries via Chat IA.
Why a private blockchain inside the GoDataX ecosystem?
GoDataX Trust Ledger adds a private, enterprise-controlled blockchain layer to register data assets, record immutable evidence, and enforce governance rules through smart contracts. It creates a tamper-proof audit trail for assets, versions, approvals, and critical executions, enabling trust, compliance, and traceability by design.
Private network control
Run on a private network with controlled nodes, permissions, and enterprise security, no exposure to public chains.
Immutable audit trail
Evidence becomes tamper-proof: who changed what, when, why, and which pipeline/model produced the output.
Smart contracts for governance
Encode rules and approvals as smart contracts (policies, sign-offs, SLAs, critical thresholds, lifecycle states).
Proof of integrity (hashing)
Register hashes of datasets, reports, and model outputs to prove integrity without storing sensitive data on-chain.
Designed for compliance & disputes
Create defensible evidence for audits, regulators, and internal risk, reducing disputes and accelerating approvals.
Smart Contract Methods (Core APIs)
RegisterDataAsset
Registers a data asset on-chain with metadata pointers, hash proofs, owner, classification, and lifecycle state.
- Result: immutable asset identity + provenance anchor.
- Benefit: trusted registry for governance, quality, and monetization.
GetDataAsset
Retrieves the latest on-chain state of an asset: owner, version, status, proofs, and linked evidence references.
- Result: real-time trust lookup for pipelines, AI, and users.
- Benefit: faster decisions with verified information.
GetAuditDataAssets
Returns an auditable history for assets (events, versions, approvals, status changes, executions) with timestamps.
- Result: end-to-end traceability across governance, quality, and AI outputs.
- Benefit: audit-ready evidence + incident investigation in minutes.
GoDataX Strategic Discovery
GoDataX Strategic Discovery is an executive, decision-first engagement that turns strategy into governed data products, analytical/statistical models, and monetization-ready intelligence. It applies the GoDataX DT Toolkit with Data Product and Data Science workflows to populate GoDataX CTP metadata, align stakeholders, and accelerate activation from opportunity discovery to production decisions.
Engagement formats
A structured delivery model from discovery to monetization, with clear timelines and outcomes.
- Executive Discovery (2–4 weeks)
- Data Product Design Sprint (4–6 weeks)
- Monetization & Scale (6–12 weeks)
Strategy → governed execution
Converts business goals into executable data strategy with governance embedded by design.
- HMW portfolio & opportunity radar
- Policy → rules → controls approach
- Metadata-first delivery (GOV + Tech + SPU)
CTP roadmap (phases)
A complete GoDataX CTP roadmap that guides the implementation and ensures traceability.
- Discovery → Classification → Policy
- Rules → Metadata GOV → Business Rules
- Technical Metadata → Semantics → SPU
- Opportunities (Models / AI / Monetization)
Deliverables & value assets
Concrete artifacts ready to activate decision-making and unlock monetization.
- Data Product Canvas (approved)
- Data Science Workflow (validated)
- MVP model definitions + embedded rules
- APIs / Scores / Benchmarks + ROI dashboard
GoDataX MCP
GoDataX MCP is a Model Context Protocol server that connects any MCP-compatible AI client, Claude Desktop, Claude Code, n8n’s MCP node, and others, directly to the GoDataX CTP platform. It turns metadata, semantics, quality, governance, trust and agent orchestration into tools an AI can query natively, connecting AI to the world of your governed data.
Universal AI connectivity
One standard protocol instead of custom integrations for every AI assistant or automation tool you adopt.
- Claude Desktop & Claude Code
- n8n MCP node & other MCP clients
- Runs over stdio, drop-in configuration
Full CTP layer coverage
Every layer of the GoDataX framework exposed as callable tools, so AI agents reason over real, governed context.
- Metadata, SPU semantic catalog & knowledge graph
- Data quality & governance status
- Trust Ledger & agent orchestration
Secure & read-only by design
Built so AI clients can explore and recommend without ever putting your data or blockchain state at risk.
- Guarded SQL/Cypher, no writes
- No hardcoded credentials
- Nothing touches Firebird, Neo4j or the ledger
Faster, better-informed decisions
Every conversation with your AI assistant becomes a conversation with your governed data estate.
- Instant answers on assets, quality & governance
- Heuristic DQ & governance recommendations
- Less integration effort, more time to value
GoDataX Human Seven (H7)
GoDataX Human Seven (H7) puts people, not just processes, at the center of the CTP. It listens to how employees really feel and function, combining validated psychometric instruments with physiological signals (cardiac coherence / HRV) to understand motivation, resilience, and adaptability as they truly are. The goal isn’t to score people, it’s to notice early when someone needs support, guidance, or a change of pace, and turn that understanding into real care: coaching, mentoring, wellbeing referrals, and personalized development paths, handled with the same privacy and governance as any sensitive data in GoDataX.
Understanding what truly motivates each person
Validated engagement, hardiness, and adaptability scales reveal what drives, energizes, or quietly wears someone down, so leaders can have better, more caring conversations instead of guessing.
Spotting stress and burnout before they take a toll
Cardiac-coherence (HRV) readings, combined with how people describe their own wellbeing, help tell a hard week apart from a pattern of exhaustion, early enough to offer support and prevent burnout.
Turning weak points into a plan for growth
Strengths, gaps, and extreme profiles are mapped not to label anyone, but to point to the next right step: coaching, mentoring, training, or a referral to professional support.
Care that respects privacy and dignity
Every score and session lives inside GoDataX Metadata’s Knowledge Graph, protected by Governance and Assurance: access-controlled, auditable, and compliant (LGPD/GDPR/PDPL-ready), so sensitive human data is handled with the same care as the people behind it.
Context that keeps recommendations human
GoDataX SPU gives meaning to every score, so “low resilience” or “high engagement” is read in context by HR and leadership, never reduced to a cold number an algorithm spits out.
From insight to real support
Findings reach HR and leadership as clear, actionable recommendations, wellbeing check-ins, development plans, coaching or support referrals, delivered through the same governed Agents and dashboards used across GoDataX, with a full audit trail.
Initial Setup
An end-to-end initial setup that transforms business strategy into executed data value, combining strategic design, pipeline and model engineering, and the technical enablement of metadata, services, and APIs required to support GoDataX Components. It is offered under two models: in-house execution or +guided execution (enablement model).
Data-Driven Strategy & Value Engineering
From strategy to value: designing governed data pipelines and analytical models aligned with enterprise monetization goals. (Business Strategy High-Level)
- Strategic Discovery & Design Thinking
- Value & Data Architecture Definition
- Pipeline & Transformation Design
- Analytical & Statistical Modeling (when applicable)
- Governance & Monetization Enablement
Strategic Deliverables & Value Assets
Design thinking that turns strategy into governed data pipelines, analytical models, and monetizable data products. (Business Strategy High-Level)
- Business Canvas & Strategic Map & Value Proposition
- Designed Data Pipelines (Silver / Gold Layer)
- Designed Statistical and analytical models (Analytics ML Layer)
- Formalized transformations and business rules
- Designed Data products ready for monetization
- Foundation for Quality, SPU, XAI, and continuous Governance
- Defined Technical metadata model
- Defined Governance metadata model
- Defined SPU metadata model
Strategy-to-Value Execution
Connection to the data transformation layer for metadata extraction and preparation. (Technical Implementation Enablement)
- Connection Data Pipeline & Transformation Design
- Connection Analytical & Statistical Model Enablement
- Connection Data Product Design & Monetization Enablement
- Connection XAI-Ready Semantic Layer — LLMs and RAG consume meaning, context and constraints, not raw tables
- Foundation for Quality, SPU, XAI & Continuous Governance
- Scope limited to one business domain, one dataset, and one end-to-end pipeline
Core Asset
The semantic and cognitive core that turns governed data into trusted intelligence. (Technical Implementation Enablement — Hosted by TwoData.ae or Self-hosted)
- Build the technical metadata model
- Build the governance metadata model
- Build the SPU metadata model
- Develop DDL scripts for the metadata models
- Develop DML scripts to populate the metadata models
- Host and operate the metadata platform
- Implement services, Unix environments, tools & APIs
- Metadata services and integration APIs
- Blockchain connectivity services and APIs
- n8n services and integration APIs
* The initial setup is activated upon the acquisition of any of the four core GoDataX components: Quality, Governance, SPU or Agents.
GoDataX Compliance Matrix
The GoDataX model covers 100% of DAMA-DMBOK areas and goes beyond. DAMA defines what to govern. GoDataX defines how to execute, measure, and prove.
DAMA-DMBOK Coverage
| DAMA Area | Processes Covered |
|---|---|
| Data Governance | Ownership, policies, decision rights, risk, executable governance, remediation |
| Data Architecture | Logical & physical architecture, environments, flows, integration |
| Data Modeling & Design | Conceptual & logical modeling, semantic relationships, asset mapping |
| Data Storage & Operations | Execution, monitoring, backup/restore, operational evidence |
| Business Glossary & Dictionary | Glossary terms, shared definitions, semantic alignment |
| Data Quality | Quality rules, metrics, execution, exceptions, remediation |
| Data Security & Privacy | Classification, purpose, consent, retention, DSAR, breaches |
| Data Warehousing & BI | Metrics, KPIs, reporting, evidence-based decision support |
| Advanced Analytics & AI | Model governance, risk, monitoring, auditability |
| Document & Content Management | Evidence management, audit trail, traceability |
Regulatory & Compliance Coverage
| Area | Regulation / Framework | Country or Region |
|---|---|---|
| Privacy & Data Protection | LGPD | Brazil |
| Privacy & Data Protection | GDPR | Europe (EU) |
| Privacy & Data Protection | CCPA / CPRA | USA (California) |
| Privacy & Data Protection | PDPL | United Arab Emirates / GCC |
| Information Security | ISO 27001 / 27002 | Global |
| Cybersecurity | NIST CSF | USA / Global |
| Banking Risk Data | BCBS 239 | Global |
| Financial Controls | SOX | USA |
| AI Governance | ISO 42001 | Global |
| AI Regulation | EU AI Act | Europe (EU) |
GoDataX Cost Reduction & Efficiency Gains
Typical outcomes from governed metadata + quality execution + SPU semantics + audit-ready evidence.
1. Operational Cost Reduction — 15–30%
- Less rework, faster root cause, fewer manual reconciliations
- Reusable rules & controls across domains
- Reduced run failures and incident load
2. Compliance & Audit Cost Reduction — 30–60%
- Automated evidence, immutable trails, audit-ready by design
- Policy → control → execution → proof traceability
- Fewer audit cycles, less manual documentation
3. AI & Advanced Analytics Optimization — 20–40%
- Governed access + semantic RAG reduces waste
- Higher model reliability (less drift, fewer retries)
- Faster delivery with consistent definitions
4. Tooling & License Consolidation — 10–25%
- Fewer overlapping platforms and redundant tooling
- Shared execution layer for controls and evidence
- Standardized operations and monitoring
5. Avoided Wrong Decisions — De-risked (Revenue at risk)
- Consistent KPIs and definitions across the enterprise
- Trusted context at decision time (not post-mortem)
- Reduced pricing/forecast/investment errors
Greatest financial advantage of well-implemented metadata
Dramatically reduces the cost and risk of wrong decisions while accelerating correct decisions at lower marginal cost. Metadata turns decisions into assets, not bets.
Without — Decision as risk
Conflicting metrics, low trust, rework
With — Decision as asset
Reusable definitions, executable rules
With — Faster cycle time
Less meetings, faster approvals
With — Lower risk
Ownership, rules, automatic evidence
With — Data as capital
Products, chargeback, predictable AI ROI
| €5M annual data/analytics spend | → 15–25% savings (€750K–€1.25M) |
| Expected payback | 9–15 months |
This page mirrors, in full, the product catalog published at twodata.ae/products.html. For pricing, live demos, and engagement scoping, contact TwoData FZCO directly.
