How multi‑model AI makes LLMs ready for production
Each model brings specialized expertise. Semantic resolves entities and relationships, Behavioral defines normal activity, and Knowledge converts findings into actionable intelligence. Together, they deliver repeatable, high-fidelity outcomes without the guesswork or cost of LLM-only approaches.
Structured context available when needed
The Semantic Model builds and maintains relationships between identities, resources, and actions, creating a living map of your environment for fast, precise reasoning. It stores context in a structured form, so the system interprets intent, understands dependencies, and reacts with clarity instead of guesswork. You gain faster decisions, higher fidelity outputs, and a foundation that strengthens as complexity grows.
See behavior shifts before they are a real threat
The Behavioral Model continuously establishes what “normal” looks like across every entity, including users, identities, resources, and devices, and quantifies deviations using explainable anomaly scores. Rather than relying on single-dimensional baselines that generate false positives, it evaluates multi-dimensional co-occurrence across factors such as location, time of day, entity attributes, and associated risk to produce comprehensive and accurate anomaly scoring.
LLM reasoning backed by facts, business context, and historical outcomes
The Knowledge Model blends deep technical expertise, curated external intelligence, and intimate awareness of your environment. It draws from LLM reasoning, historic decisions, and hard-coded business rules to understand how your applications, infrastructure, and policies actually operate day to day. High-level intents are broken down into precise checks across the Semantic and Behavior layers, then reported back as clear summaries with supporting evidence, so analysts and auditors see not only the answer but the why behind it.
Deterministic and governable outcomes you can defend
Multi-model AI replaces ad-hoc prompting with governed reasoning for consistent, auditable results. The Semantic, Behavior, and Knowledge Models work within your guardrails, with explicit data scope, curated context, and full logging. You get focused, human-like interaction tailored to your business, not a general-purpose chatbot.
Frequently asked questions
How does multi‑model AI make LLMs more deterministic?
How is the behavioral model different from UEBA?
How is the Knowledge Model different from “just an LLM”?
Will this work with my existing SIEM/EDR/IDP stack?
What guardrails keep the system safe?
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