SOVEREIGN COGNITIVE SYSTEM
SAVANT-AI IS A SOVEREIGN ENTERPRISE COGNITIVE SYSTEM
It acts as the sovereign brain of your organization – the Enterprise Cognitive System installed in the customer's infrastructure, which connects ERP, MES, PLM, WMS, CRM, and hundreds of other systems into a single controlled nervous system of the organization.
It is designed for large industrial and logistics companies and regulated sectors (finance, energy, defense, medicine, public administration) where data cannot be "moved" to the cloud and decisions must be fact-based and fully auditable.
PLATFORM OVERVIEW
SAVANT-AI is a sovereign Enterprise Cognitive System that acts as the local brain of an organization and a cohesive nervous system across all IT systems.
The platform operates as an on-premise appliance on NVIDIA HGX B300 architecture, in full network isolation (air-gap), so that all AI processes take place in your data center—on your data, models, and policies.
SAVANT-AI uses an agent-based AI architecture: instead of a single chatbot, it launches an orchestra of specialized domain agents under a central Orchestrator Core, based on Llama-3 405B, among others.
The system not only answers questions, but also actively manages the flow of knowledge, breaks down complex business problems into tasks, and proposes decision recommendations for operations and management.
THE PROBLEM IT SOLVES SAVANT-AI
In large organizations, SAVANT-AI reduces the effects of information silos and "information friction" that previously slowed down decisions and hampered innovation. Data remains scattered across ERP, PLM, MES, WMS, CMMS, CRM, DMS, and hundreds of local repositories, with each system speaking its "own language," requiring manual translation and interpretation by experts.
As a result, organizations experience decision-making inertia: managers, engineers, and planners wasted a significant part of their day searching for, verifying, and comparing information from multiple sources, which translated into real costs of lost productivity amounting to millions of euros annually. At the same time, companies faced the phenomenon of the "silver tsunami" – the departure of the most experienced experts, whose tacit knowledge was not captured in systems, so that with each generational transfer, companies actually lost critical know-how.
With volumes measured in petabytes, organizations also felt the "physics of data" (Data Gravity): moving data to the cloud is costly, slow, and risky.
SAVANT-AI overcomes these challenges: it reduces information friction, consolidates and secures intellectual capital, and delivers AI effects while maintaining data locality and sovereignty.
ARCHITECTURE AND OPERATION
SAVANT-AI ARCHITECTURE - implemented as an "integrated digital nervous system for corporations," with a local SAVANT-AI APPLIANCE unit based on NVIDIA HGX B300 with a large VRAM pool and NVIDIA BLACKWELL & TEE (TRUSTED EXECUTION ENVIRONMENTS) support as its physical foundation.
THE SYSTEM OPERATES IN COMPLETE ISOLATION AIR GAP - which means that critical cognitive processes are physically separated from the Internet, and any use of external models takes place only in strictly controlled, anonymized contexts.
IN THE LOGICAL LAYER SAVANT-AI HAS BEEN DIVIDED INTO SEVERAL KEY COMPONENTS - Cameleoo interface, Cognitive Governance Gateway, Orchestrator Core, domain agent team, knowledge repository (Knowledge Hub), Corporate Context Buffer, MCP nodes for integration, infrastructure manager, and cognitive supervision and audit module (Sentinel).
FIVE LAYER TECHNOLOGY STACK includes a presentation, perception, and intent layer, a cognitive orchestrator, an integration layer with operational agents, and a knowledge and unstructured data layer with the RAG 2.0 engine—all running locally on an appliance, ensuring low latency and full auditability.
AGENTIC AI ECOSYSTEM launches specialized agents connected to ERP, PLM, MES, WMS, CMMS, CRM, and other systems, which work on the permissions of a specific user.
ORCHESTRATOR CORE decomposes complex business questions into sub-tasks, delegates them to agents, and then synthesizes and cross-verifies conclusions, reducing the risk of AI hallucinations and errors.
This system creates a closed loop from understanding the user's intent, through planning the thought process (chain-of-thought), acquiring live data from transactional systems, to delivering a verified, explainable answer with a full source trail.
TEN-LAYER COGNITIVE ARCHITECTURE
In implementations SAVANT-AI a five-layer technology stack was used to organize the processing logic:
PRESENTATION LAYER CAMELEOO – ADAPTIVE USER INTERFACE tailoring the form of presentation (text, tables, knowledge maps, visualizations) to the role of the recipient (operator, engineer, CFO, board member).
PERCEPTION AND INTENTION LAYER – NLU MODULES, which have learned natural language with industry and engineering jargon, identifying the business objectives of queries and task priorities.
COGNITIVE ORCHESTRATOR – THE HEART OF THE SYSTEM, which creates cross-domain query plans on the fly, manages agents, source selection, and inference sequence.
INTEGRATION LAYER AND OPERATIONAL AGENTS – a set of specialized agents connected to ERP, PLM, MES, CRM, DMS, and other systems, operating on the basis of specific user permissions.
LAYER OF KNOWLEDGE AND UNSTRUCTURED DATA – RAG ENGINE, which collects the organization's digital footprint in vector databases and connects documents, emails, procedures, and event logs into a coherent semantic space.
The entire stack runs locally on the Appliance, which minimized latency and eliminated "black boxes" – every processing step was logged, making responses auditable at the level of the sources, agents, and policies used. This deterministic "Factual Grounding" path distinguished SAVANT-AI from typical generative cloud solutions, which often operated statistically and without full traceability.
ECOSYSTEM AGENTIC AI
SAVANT-AI implemented the Agentic AI paradigm: instead of a single, universal model, the system launched an orchestra of specialized agents representing specific domains of knowledge and source systems.
Orchestrator (based, among other things, on Llama-3 405B) breaks down complex business questions into subtasks and forwards them to the appropriate agents, who process the data in their areas of expertise.
Each agent received their own tools (e.g., access to a specific ERP, PLM, CMMS module, or external knowledge source), and their conclusions were then synthesized and cross-verified, which significantly reduced the risk of hallucinations.
Adding new areas of knowledge does not require rebuilding the system—simply add another agent to the existing orchestration, ensuring natural scalability of the solution.
GOVERNANCE, SECURITY, AND SOVEREIGNTY
SAVANT-AI It stands out with its highly developed management and security layer, focused on ensuring full information sovereignty.
The COGNITIVE GOVERNANCE GATEWAY it acts as an intelligent, semantic firewall – analyzing not only the content of the query itself, but also the intent, session context, and data class to which the response could refer.
EVERY DATA SET IN THE ORGANIZATION IS CLASSIFIED (e.g., Public, Internal, Confidential, Top Secret), and the Governance Gateway enforced an Internet Isolation policy for confidential data – queries requiring access to such information were not allowed to leave the local network perimeter.
SEMANTIC INTENT FILTERING TECHNOLOGY AND DEEP SOVEREIGNTY MODE were used, in which cognitive processors were logically and physically isolated from any external network interfaces when working on critical data.
MULTI LAYERED ACCESS MODEL MATRIX includes RBAC, ABAC, MAC, ReBAC, PBAC, RAdAC, and Break-the-Glass/Emergency RBAC modes, embedded directly in the cognitive layer, with full logging and auditing.
PROTECTION MECHANISMS include data anonymization (Autonomous Data Scrubbing), dual Sentinel cognitive supervision, killswitch, and Emergency Isolation, additionally implemented in trusted TEE execution environments on Blackwell accelerators.
REALTIME AI AUDITING records query semantics, models used, agents, data sources, and policies triggered, creating an audit trail for management, the board of directors, and compliance functions.
ACCESS CONTROL MODELS
SAVANT-AI supports a multidimensional access model matrix that goes far beyond the classic RBAC model:
RBAC – roles reflecting the organizational structure (e.g., Process Engineer vs. Production Planner), determining the basic view of knowledge.
ABAC – control based on attributes such as location, time, device type; in practice, access to sensitive financial reports was restricted, for example, to the company network and working hours.
MAC – mandatory access control modeled on classified information standards; the "Top Secret" label blocked access even to board members without the appropriate clearance.
REBAC – relationship-based control, where access to project documentation depended on the user's actual role in the project team.
PBAC – control based on policies written in a language similar to natural language (e.g., prohibition of synthesizing R&D data with contractor data without compliance approval).
RADAC – adaptation of permissions to the current level of risk; in case of suspicious activity, the system tightened requirements (e.g., MFA, narrowing of responses).
BTG E RBAC – Break the Glass and Emergency RBAC modes, which enable temporary extension of privileges in emergency situations, with full logging and auditing.
The system does not maintain a separate, independent permissions database; instead, it maps identities and roles from source systems (Identity Mapping), ensures consistent permissions across the ecosystem.
The Cognitive RBAC mechanism allows you to define "cognitive roles" that limit or extend the scope of synthesis at the response level (e.g., an auditor could see data in full detail, but only locally, without the ability to export it to external models).
PROTECTION MECHANISMS AND AUDIT
Protective mechanisms: data anonymization (Autonomous Data Scrubbing), dual cognitive supervision (Sentinel), emergency shutdown, and emergency isolation, which automatically blocked sessions and access in the event of attempts to extract know-how.
Critical operations are performed in trusted execution environments (TEEs) in HBM3e memory on Blackwell accelerators, ensuring separation at the silicon level, not just at the software level.
Real-time AI audit: the system analyzes the semantics of queries and responses, identifying attempts at social engineering attacks or unusual data retrieval patterns, and in case of doubt, switches to "restricted access" mode, referring the matter to a cluster of experts (Human in the Loop).
Every use of emergency mode, every block, and every knowledge flow is recorded in an inviolable log, which serves as the basis for reports to oversight and compliance services.
BUSINESS AND ECONOMIC BENEFITS
SAVANT-AI implementations have been described in terms of TEI and classic ROI/NPV metrics – an investment in a local ECS supercluster will generate an NPV (depending on the size of the company) ranging from several to tens of millions of euros over a period of several years. This is mainly due to the recovery of working time for highly qualified specialists and the reduction of costly decision-making errors.
Key value streams include: reduced response time to operational incidents, improved supply chain stability, optimized production indicators, faster onboarding of new employees, reduced errors in bidding/tendering processes, and better protection of trade secrets.
From a strategy perspective, information sovereignty has become a competitive advantage in its own right—organizations have built their own unique models and agents saturated with specific know-how that they do not share with any cloud provider or competitor.
WHO IS SAVANT-AI FOR?
SAVANT-AI was developed for manufacturing and logistics companies and sectors with high regulatory requirements (finance, energy, defense, medicine, government and public institutions) that operate with huge volumes of data and cannot afford to move it to the public cloud.
The product meets the needs of C-level executives (CEO, CFO, CIO/CTO, CLO/Compliance), COOs, and heads of competence centers who need a unified, secure "corporate brain" for all AI initiatives.