
Frequently asked questions
Most systems use models of this scale as monoliths. We treat Llama-3 405B as the Logical Core (Super Agent), which does not “remember” data but has the highest planning capabilities. It decomposes Management Board queries into tasks for smaller, specialized 70B agents, which guarantees precision unavailable to systems based on a single model.
In high-tech industry, “secure cloud” is an oxymoron. Physically cutting off the system from the Internet (Air-Gap) is the only 100% barrier against supply-chain attacks and silent data leakage (Data Seepage) to external suppliers. In our architecture, sovereignty is a matter of physics, not just a promise.
When policy allows the use of public LLMs (e.g., for market trend analysis), the system initiates the NLU anonymization process. All values, proper names, and project codes are replaced with synthetic tokens. The outside world receives only the “logical skeleton” of the query, never learning the subject of the GMLC analysis.
Yes, it is called the Corporate Context Cache. The system remembers not only facts from documents, but also the entire course of decision-making processes in the company. Thanks to this, a new strategic analysis can refer to the Management Board's findings from the previous quarter, maintaining the continuity of corporate thinking.
Sentinel is an independent oversight process that audits the results of fact synthesis in real time before they are displayed. It acts like a drone scanning the communication path—if it detects a risk of violating the “Deep Sovereignty” policy, it triggers a system kill switch, blocking the session.
Deep Citation is an unbreakable chain of evidence (Source Traceability). Each number in the system's response is an interactive link that opens the source document exactly on the page and paragraph from which the fact originates. This marks the ending the era of "hallucinated metrics" or "random numbers".
The system dynamically modifies the access level depending on the risk profile of the session. If a user with high privileges logs in from an unsecured location, SAVANT-AI automatically restricts the visibility of sensitive data, requiring additional authorization for the synthesis of financial facts.
In SAVANT-AI, the generation process is reversed (Reference-First Synthesis). The model first aggregates evidence from databases and only then builds a response from it. If it cannot find source evidence, the system does not guess – it reports a lack of data, pointing to an information gap in the company.
This is made possible by the power of the cognitive orchestrator (Llama-3 405B), which, thanks to advanced Natural Language Understanding (NLU), understands the user's intentions without the need for rigid commands or learning to navigate ERP/PLM systems. The employee talks to Cameleoo as if it were a live expert, while the 405B model performs the tedious work of technology orchestration in milliseconds.
Enterprise Cognitive System (ECS) does not stop at reporting "what happened." SAVANT-AI is a sovereign digital nervous system for corporations that performs active fact synthesis and deterministic knowledge orchestration. Instead of static dashboards, it offers an autonomous inference mechanism based on the Multi-Agent Domain Swarm model, which eliminates information silos and builds lasting intellectual assets for the organization.
The system radically reduces information friction, solves the problem of knowledge debt, and counteracts the effects of the "silver tsunami," i.e., the loss of unique know-how from departing expert staff (Cognitive Succession). SAVANT-AI eliminates "decision inertia" in large capital groups, providing a market advantage through microsecond access to Objective Truth.
In large organizations, data exhibits the phenomenon of "Data Gravity" – its mass and sensitivity make secure migration impossible. The on-premise model on SAVANT-AI Appliance units guarantees absolute cognitive sovereignty and silicon-level security (TEE Enclaves). Thanks to air-gap network isolation, unique recipes and GMLC strategies will never feed into competitors' public models.
No; ECS acts as a cognitive mentor and the highest synthesis instance in the Human-in-the-Loop model. The system provides recommendations based on hard evidence using the Reference-First Synthesis mechanism, but the final verification and responsibility remain with the human, whose work is freed from tedious data extraction in favor of pure strategy.
The foundation of the system is a dedicated SAVANT-AI Appliance based on the revolutionary NVIDIA HGX B300 (Blackwell Ultra) architecture. It features 2.3 TB of VRAM with KV Cache optimization, allowing for the permanent residency of the most powerful models (Llama-3 405B) and the simultaneous handling of thousands of cognitive sessions in real time.
Security is built into the system's binary code. SAVANT-AI implements Deep Sovereignty Mode and Autonomous Data Scrubbing technology, which anonymizes data before any interaction with the external network. Each inference process is monitored by an independent Sentinel Module (Cognitive Guardian), which acts as a system kill switch in emergency situations.
The standard Operational Alignment process takes 12 weeks. It includes an inventory of knowledge silos, physical installation of the Appliance in air-gap mode, semantic mapping, and calibration of the "core of truth" by GMLC Expert Clusters, which allows for measurable Proof of Value in critical processes.
The key metrics (KPIs) are knowledge debt reduction, return on assets (ROA) growth, and a drastic reduction in MTTR and MTTS (Mean Time to Synthesis) parameters. SAVANT-AI allows you to pay off the "tax on ignorance," which translates into millions in savings from eliminating R&D duplication and operational errors.
For global industry leaders such as GMLC, where owning sovereign intellectual capital is a prerequisite for market survival. The system is essential in sectors with the highest security and compliance requirements, where every second of delay or leak of engineering parameters generates critical strategic risk.
Interaction takes place through Cameleoo – a Cognitive Adaptive Interface that dynamically generates 3D decision dashboards and knowledge maps. The manager operates in natural language, and the system proactively provides alerts about compliance risks or anomalies in the supply chain, based on predictive orchestration of facts.
The SAVANT-AI architecture goes beyond standards, offering a multidimensional matrix of 7 permission models, including RAdAC (Risk-Adaptive Access Control). The system dynamically modifies access based on the session's risk profile, ensuring full auditability in accordance with NIST and ISO standards.
The main risk is the opportunity cost. Failure to implement ECS in the era of cognitive transformation condemns an organization to permanent inefficiency and erosion of know-how. Implementation risks are mitigated by the rigorous methodology of the Pilot Phase and the sovereignty of the on-premise model.
The system implements a cognitive succession process. Through continuous indexing of project notes, correspondence, and engineering decisions, SAVANT-AI digitally extracts so-called tacit knowledge. When an expert leaves, their “operational intuition” and problem-solving patterns remain within the corporate brain, available to new staff.
Knowledge debt is the hidden cost of rediscovering solutions that have already been developed in another department. SAVANT-AI acts as a debt consolidation mechanism—it identifies duplications in R&D and production, suggesting a Design Reuse strategy. Repaying this debt directly increases return on assets (ROA).
