Cogniss. Organizational know-how becomes structured knowledge for AI.

Cogniss is the Cognitive Control Plane developed by AISMA: the cognitive infrastructure that unlocks the value of an organization's assets and makes them available to artificial intelligence within a governed environment.
It profiles the archive, prepares documents, organizes knowledge into a queryable Knowledge Layer, and makes it accessible to people, systems, and AI models — preserving context, accountability, and traceability.

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The Context

Adoption is accelerating. Governance is missing.

Many organizations have already invested in data warehouses, business intelligence, analytics, and document management systems. The challenge today is not to add another reporting tool or launch a chatbot: it is to unlock the value of the archive, transforming years of documents, procedures, and technical knowledge into a genuinely usable asset. Reliability is not a feature of AI. It is an organizational responsibility.

Hallucinations: how do I verify the output?
Am I locked into a single vendor?
Do I risk losing know-how?
Am I regulatory compliant?

The Answer

Cogniss: the organization's Cognitive Control Plane.

Every organization operates according to rules, responsibilities, evaluation criteria, and knowledge that define how it works and makes decisions. Much of this expertise lives within its documents.

Cogniss makes this asset an integral part of AI systems, transforming it from a scattered archive into a structured, queryable, and coherent representation of the organization: its Knowledge Layer.

Information assets.

Organizational information — documents, procedures, reports, technical knowledge — is profiled, prepared, and organized into a coherent and shared model, capable of preserving its context, meaning, and operational value.

  • Features

Cogniss integrates documents, data, policies, and information sources into a single structured asset — the Knowledge Layer — built through the Semantic Backbone: the organization’s governed semantic view, a proprietary Knowledge Graph with domain-specific ontologies and end-to-end lineage that interprets, structures, and mediates the flow between enterprise data and AI applications, independently of the underlying models.

AI Models and Operational Rules

Artificial intelligence operates within a context defined by the organization’s own rules, responsibilities, and evaluation criteria.

  • Features

Cogniss coordinates AI models and operational logic on the prepared knowledge, ensuring that activities, analyses, and automations remain consistent with the policies, objectives, and requirements of the application domain. It is model-independent: it operates with any LLM or specialized model — GPT, Claude, Mistral, open-source solutions — replaceable without rebuilding the knowledge base (BYO-model).

Accountability and Traceability

Every output can be traced back to the documents, rules, and criteria that determined its generation. Data remains the organization’s property: the corporate corpus is always under the client’s control and confidentiality is guaranteed by design. Cogniss is delivered according to deployment models with increasing levels of sovereignty — dedicated EU Cloud, on-premise, air-gapped, or dedicated SaaS — following a security-by-design approach.

  • Features

Cogniss maintains visibility across the entire cycle, from source to output: every step is recorded in an immutable Audit Trail, with cryptographic Evidence Spans and a verifiable Reasoning Certificate, while triple-validation Quality Gates (SHACL rules) and advanced eIDAS electronic signatures make outputs defensible in audits and in court (where documents carry legal relevance). Retention is configurable for regulated environments and compliance is designed in, not added after the fact: EU AI Act, DORA, GDPR, NIS2.

Operational Experience

Access to knowledge and AI capabilities is delivered through tools designed to integrate into the organization’s daily activities. The goal is not to decide upfront whether a chatbot, a search engine, or an agent is needed. The goal is to build the Knowledge Layer that makes the organizational archive usable across all of these scenarios.

  • Features

Hybrid search, operational interfaces, dashboards, and collaborative environments enable people, analytics, workflows, and agents to draw on the organization’s information assets, maintaining continuity across people, systems, and processes.

Cogniss: your organization's AI co-worker

Cogniss brings artificial intelligence into daily work as a co-worker: it collaborates with people, enhances their capabilities, and supports teams in operational activities.

It integrates with the organization’s information ecosystem, without replacing existing applications or systems. It does not start from a single rigid use case, but from the preparation of knowledge: use cases can evolve over time — today search, tomorrow comparison, then extraction, analysis, compliance, decision support, or specialized agents.

This is why it is a progressive solution: ready-made building blocks, consulting activities, and adaptation to the client’s specific context.

1

Verifiable Outputs

Every output can be traced back to its sources, rules, and processing criteria, with trackable evidence, ensuring transparency and accountability in high-responsibility contexts.

2

Automated Reporting

Production of reports, summaries, and operational documentation through processes consistent with the organization’s policies, standards, and requirements.

3

Operational Visibility

Dashboards and analytics tools that make relevant information, activities, and performance indicators accessible for monitoring purposes.

4

Workflow Orchestration

Coordination of activities, approvals, and operational flows through configurable processes integrated into the organizational ecosystem.

5

Knowledge Management

Archive profiling, corpus preparation, and Knowledge Layer construction: centralization and valorization of the information assets, made queryable and reusable by people and AI systems.

6

No Fallback policy

When factual evidence is lacking, Cogniss does not produce an unverified output — it engages the relevant human experts and transfers the assessment to human oversight.
The autonomy of artificial intelligence must be proportionate to the risk associated with the activities it supports.

7

Audit & Compliance

Support for governance, auditability, and regulatory compliance requirements — EU AI Act, DORA, GDPR, NIS2 — through the traceability of activities and information sources.

8

Cognitive Skills

Activation of vertical capabilities dedicated to specific operational, regulatory, and organizational domains.

Skills

Vertical capabilities designed to apply artificial intelligence across the primary enterprise domains.

Each Skill combines specialized expertise, operational context, and industry requirements within dedicated solutions for finance, legal, operations, and sustainability.

Trade Finance — End-to-end management of the commercial credit and debt financing cycle: KYC/AML document validation, real-time limit monitoring, automated on-boarding. Differentiator: native AML/KYC/PSD2 compliance, automatic three-way match.

Digital Law Firm — Cognitive infrastructure with specialized agents for discovery, retrieval, reasoning, and document production; every output anchored to verifiable sources. Differentiator: triple Quality Gates, Reasoning Certificate, NO-FALLBACK.

Credit & Regulatory Compliance — Platform for banks and NPL/UTP servicers subject to DORA: portfolio management, document automation, and regulatory compliance with certified data lineage. Differentiator: integrated DORA framework, end-to-end lineage.

Regulatory Compliance Automation — Automation of the multi-perimeter compliance cycle (GDPR, Legislative Decree 231/2001, NIS2, ISO): ingestion of official sources, impact mapping, generation of EU AI Act-compliant drafts. Differentiator: four-level taxonomy, Reasoning Certificate on drafts.

HR & Staffing Intelligence — Governance of the recruiting cycle and contract administration: explainable semantic matching, automated CCNL compliance, organizational Knowledge Graph. Differentiator: Explainability Tag (GDPR), CCNL CheckCompliance.

Manufacturing Intelligence — ERP/CRM/PM integration for forecasting and automatic generation of technical proposals, with archive anchored to the Knowledge Graph. Differentiator: forecasting with audit trail, live technical archive.

Space Planning & Generative Architecture — Automated preliminary space design: variant generation, validation of regulatory and structural constraints, structured BIM outputs. Differentiator: automatic SHACL validation, Digital Twin foundation.

Marine Environmental Monitoring — Marine and coastal environmental monitoring that fuses IoT data, RADAR/SAR satellites, and drones: monitoring, prediction, and governed early warning. Differentiator: 72h early warning, multi-sensor data fusion; validated in protected marine areas.

Smart Farming Ecosystem — Digital ecosystem for livestock farming and precision agriculture: computer vision, multi-level biometric validation, 40+ real-time KPIs, and governed predictive alerts. Differentiator: confidence synthesis, edge computing.

SecurityCognitive Security — Non-invasive cognitive add-on built on top of existing PSIM platforms: natural language search, operational assistant, event classification, and video analysis. Differentiator: progressively activatable intelligence-as-a-service, zero false negatives, EU AI Act compliance.

Smart Farming Ecosystem — Digital ecosystem for livestock farming and precision agriculture: computer vision, multi-level biometric validation, 40+ real-time KPIs, and governed predictive alerts. Differentiator: confidence synthesis, edge computing.

FAQ

A generic model has no knowledge of your organization’s rules, responsibilities, and documents, and produces outputs that cannot be verified. Cogniss makes AI work on the organization’s actual knowledge, aligned with its policies and context, and makes every output traceable.

Cogniss applies the AI co-worker model, modulating the level of autonomy based on risk, context, and operational criticality. In high-impact processes, the system engages the relevant human experts and keeps the decision-making flow permanently verifiable.

Yes. Your information assets remain the organization’s property and confidentiality is guaranteed by design.
Cogniss can be deployed on a dedicated EU Cloud, on-premise, air-gapped, or dedicated SaaS, according to your sovereignty and security requirements.

Yes. Cogniss integrates with existing data warehouses, business intelligence, analytics, and document management systems, without replacing them: it unlocks the value of their contents by incorporating them into the Knowledge Layer.

To unlock the value of years of documents, procedures, and reports — often scattered and difficult to reuse — transforming them into a shared, queryable, and comparable knowledge base, usable by people, analytics, workflows, and AI systems.

No. Cogniss is model-independent: it operates with any LLM or specialized model — GPT, Claude, Mistral, open-source solutions — replaceable without having to rebuild the knowledge base.

The value lies not in a single application, but in a reusable knowledge base on which multiple scenarios can be activated over time. With Cogniss, every project starts from ready-made building blocks and enriches the shared knowledge base: subsequent projects become faster, more cost-effective, and more reliable, and the return grows rather than resetting at the end of each project.

By not starting from a rigid use case, but from the preparation of knowledge, and validating value within a controlled perimeter before scaling (Discovery → Proof of Value → Production). Reusable building blocks reduce marginal costs and lower risk at every step.