DEMÍX / Perspectives
Perspectives
Product updates, releases and field notes from the platforms — published as they ship.
Sovereign infrastructure for mission-critical AI
Sovereign AI requires sovereign ground: compute and data under national jurisdiction, with determinism as a property and predictable latency on known paths.
Read update →Encrypted Multi-Jurisdiction Data Fabric
Your data where you dictate, with the resilience mission-critical operations demand: an encrypted fabric across owned facilities, hot replicas, and verifiable integrity in every jurisdiction.
Read update →Verified Continuity: Byte-for-Byte Backups and Measured Recovery
A continuity plan that has already been executed, not merely written: full integrity verification and restoration drills with measured, not estimated, times.
Read update →Local Inference: AI Cognition Without External Dependency
Language models operating on infrastructure the organization owns, under its own jurisdiction and control, for teams that cannot route critical decisions through foreign APIs.
Read update →24/7 observability with direct alerting: a silent failure is a double failure
Services, replicas, backups, disks and the public edge under continuous watch, with alerts reaching the on-call operator within minutes. Serious infrastructure keeps an eye on itself.
Read update →Elastic Compute for Training and Adversarial Simulation
On-demand compute capacity for cyber ranges, blue/red exercises and agent training — the permanent laboratory behind a defense that adapts.
Read update →Demix × Zendrix: the complete stack of sovereign autonomous defence
Infrastructure and cognitive layer, from metal to decision, under a single contractual responsibility. Governments and critical operators stop stitching together five suppliers and start talking to one counterpart.
Read update →Engineering with a Culture of Evidence: Building Systems That Prove What They Claim
Purpose-built benchmarks, verification and audit as principle: every capability claim carries its proof. That is how we attract clients who demand rigor and engineers who value it.
Read update →Knowledge infrastructure: semantic search at scale
The layer that turns archives into operational knowledge: hybrid search — lexical, vector, and graph — over hundreds of thousands of documents, with migrations verified at object level and auditable integrity.
Read update →Persistent memory and provenance in AI systems
What separates an assistant from an entity with continuity: long-term memory with verifiable provenance, separation between fact and inference, and identity that persists across sessions — recent advances of the Camile AI platform.
Read update →Governed agency: autonomy with sandbox, budget, and audit
How to give AI systems real agency without giving up control: isolated execution, resource budgets, independent review, promotion behind a test gate, and automatic rollback — the Demix governance model for entities.
Read update →Uncertainty is not weakness. It is a contract.
A forecast without a tested margin of error is not a promise — it is noise with confidence attached. In release R84 of the Camile World Model, the system relearns from the client's own most recent events: when the world changes pattern, the margin of error adjusts, with a minimum number of cases so it does not become unstable. And the science comes with a band, not a point: we repeated the experiment eight times, with different initial data, and the first result turned out to be a rare case — not the rule.
Read update →The Demíx intelligence has evolved: a new generation of its world model
Demíx Tecnologia has incorporated a new evolution of its world model: more context before acting, a clearer distinction between real happenings and effects of its own observation, and uncertainty handled with more sophistication — the technological base for the next generation of intelligent systems.
Read update →Demíx intelligence has evolved: one world, many entities — and science that verifies itself
The new generation of the Demíx platforms' world model sustains multiple entities over one world, exchanges evidence with proof of integrity, and took the model's scientific cycles to real public health and climate data.
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