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Semantic and operational context
We represent meaning, entities, relationships, processes, rules, criteria and evidence.
GenInContext™ · GIC
GenInContext: an operational foundation of knowledge and context for governed AI
GenInContext™ is Connecthink's reusable technology framework for turning data, documents, processes, rules and expert knowledge into a governed foundation that people, assistants, agents and other AI solutions can reuse. It can be implemented with Connecthink, with integrators or jointly with client teams, depending on the scope and maturity of each project.
Models provide generation and reasoning capabilities. Knowledge and context determine the reliability, traceability and real-world usefulness of AI.
Core principles for running AI with context and control
GIC reuses a shared core of capabilities to accelerate new use cases without losing consistency, traceability or control.
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Governance, explainability and auditing
Sources, provenance, permissions, applied criteria, traceability and verifiable evidence.
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Human oversight and validation
Human-in-the-Loop wherever risk, criticality or knowledge quality requires it.
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Reuse and expansion of the CDT
Validated knowledge is versioned and expanded domain by domain for new use cases.
Open architecture: the same foundation can power GIC solutions or serve other platforms through APIs, endpoints and MCP.
Functional architecture
Knowledge, specialized intelligence and operations on a shared foundation
The Knowledge Foundation is reused; agents and operational capabilities adapt to the domain, the process and the criticality level of each use case.
Core platform
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Knowledge Foundation
Builds the Cognitive Digital Twin: a shared, governed representation of knowledge, its relationships, evidence, criteria, provenance, access and lifecycle.
- Relevant information sources
- Semantic structuring of the domain
- Verifiable relationships and provenance
- Governance, access and lifecycle
Agent layer
AI
AI Specialists
Agents that use governed knowledge and context to answer, analyze and support tasks within a domain.
- General-purpose knowledge capabilities
- Domain-specific specialists when they add value
- Contextual interpretation
- Controlled integration with external capabilities
Vertical solution
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Solutions & Actions
Operational capabilities configured or developed for each process, system and criticality level.
- Alerts, signals and recommendations
- Human-in-the-Loop
- Agent integration and invocation
- Actions on authorized systems
Specialized and operational capabilities are not universal or enabled by default: they depend on the design, authorizations and implementation of each solution.
Capabilities
From organizational knowledge to operational, governed AI
GenInContext separates knowledge management, context building and operational use, while keeping a shared lifecycle.
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Knowledge engineering
Knowledge Engineering
Turns scattered information and expert knowledge into a shared, coherent and governable representation of the domain.
- Meaning and relationships
- Evidence and provenance
- Validity and permissions
- Reconciliation and validation
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Context engineering
Context Engineering
Adapts knowledge to each request, user, agent and usage condition to provide only the relevant, applicable, authorized and traceable context.
- Evidence and relationships
- Criteria and policies
- Access and provenance
- Usage limits
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Operational use
Governed AI in operation
Assistants, agents and solutions use that context with evidence, permissions, traceability and human oversight to answer, recommend or take actions as each case requires.
- Answers and recommendations
- Workflows and actions
- Human-in-the-Loop
- Ability to abstain
Shared lifecycle
Managing and evolving knowledge
Knowledge stays up to date, validated, versioned and auditable as the organization's sources, criteria, processes and needs change.
Every domain you add leaves a reusable capability
GIC lets you evolve domain by domain without having to model the entire organization from the start.
Fragmented information
Isolated documents, data and knowledge.
Findable knowledge
Information organized and accessible through contextual search.
Connected knowledge
Entities, events, documents and sources within a shared context.
Operational knowledge
Reconciled, authorized and traceable, ready for agents and decisions.
Your organization, turned into an operational foundation for AI
GIC is not just a chat with documents: it turns information, knowledge, processes and organizational judgment into a reusable foundation for running AI with real context.
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Structured understanding of knowledge
Identifies entities, relationships, metadata, terminology and context while preserving lineage and permissions.
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Operational criteria and logic
Incorporates rules, processes, validations and criteria that determine how AI should operate.
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Reusable organizational memory
Knowledge is versioned and ready for new assistants, agents, automations or external platforms.
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Evidence, explainability and traceability
Results linked to sources, context, criteria and execution steps for validation, auditing and compliance.
Evidence before the answer
Operational trust does not depend only on AI giving an answer: it depends on what it knows, where it knows it from, what limits it has and who authorizes turning it into action.
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Evidence before the answer
The solution can require the necessary evidence to be retrieved and validated before producing or displaying a result.
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Governed abstention
When grounding is insufficient or contradictory, GIC can retrieve more, change route, escalate or abstain.
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Explainability and auditable control
The result can be linked to evidence, criteria and execution steps tailored to each role.
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Human-in-the-Loop
Human validation during onboarding, evidence review or critical actions, depending on the case.
Security, privacy and traceability by design
Sovereignty is not just about where the technology runs, but about who controls data, knowledge, models and integrations.
Data and knowledge under the organization's control
GenInContext is designed so that the organization keeps control over its data, knowledge, permissions, models and integrations. The deployment model adapts to each project's requirements: client tenant, private cloud, hybrid architecture or on-premises.
When external services are used, the architecture and policies defined for the solution control what information may leave, to which service and under what conditions.
Technological sovereignty
GIC is LLM-independent and designed to preserve the ability to replace components without losing continuity of the cognitive asset.
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GDPR
Privacy, data minimization and access control depending on the solution.
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ENS-ready
Controls and evidence geared to public-sector deployments under Spain's National Security Framework (ENS); this is not a certification in itself.
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ISO 27001 aligned controls
Design based on auditable controls and processes.
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AI Act / audit-ready
Traceability, human oversight, evidence, change management and abstention to support alignment.
Compliance and certifications depend on the final solution, the deployment model, the components used and the scope agreed with each client.
Frequently asked questions
Short answers to the most common questions about GenInContext.
What is GenInContext?
GenInContext is Connecthink's reusable technology framework for turning data, documents, processes, rules and expert knowledge into a governed foundation that people, assistants, agents and other AI solutions can reuse.
What is a Cognitive Digital Twin?
It is a governed representation of an organization's knowledge, context, processes, rules, evidence and criteria. It is not just a database or a document search engine: it models how a domain works so that AI can operate with real context.
What is the difference between Knowledge Engineering and Context Engineering?
Knowledge Engineering builds and maintains persistent, governed knowledge. Context Engineering selects, for each task, the minimal, relevant, authorized and traceable context that the model, agent or workflow needs.
Does GenInContext replace my agent platform?
Not necessarily. GIC can provide governed knowledge and context to existing platforms, or deploy its own capabilities when the organization does not have them.
Can it be integrated through APIs or MCP?
Yes. The Knowledge Foundation and certain activation capabilities can be exposed through APIs, endpoints and MCP, acting as client and/or server depending on the integration.
Is it tied to a single LLM?
No. The architecture is designed to work with different models depending on policy, cost, latency, language, criticality and sovereignty requirements.
What happens if there is not enough evidence?
GIC can broaden retrieval, change route, request human validation, escalate or explicitly abstain when the context is insufficient, contradictory or not authorized.
How does it support regulatory compliance?
The solution can include traceability, access control, human oversight, evidence, change documentation and auditability. Final compliance depends on the deployment, scope and responsibilities of each project.
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Want to assess how GenInContext fits into your architecture?
We can work as a complete solution, a context layer or a capability provider for existing platforms.