Platform architecture
Each layer is independently scalable, separately upgradeable, and architecturally replaceable, without disrupting the system as a whole. From the foundation upward: memory, reasoning, orchestration, conversation, self-improvement.
Layer 01
Odysseus
Persistent memory that lets CoresNexus retain, recall, and build upon knowledge over time. Three tiers: Working (fast, volatile, sub-millisecond during task execution), Episodic (past interactions, decisions, outcomes, continuity across sessions), and Semantic (regulatory rules, industry definitions, client policies, shared across the tenant).
Layer 02
Local LLMs
Fine-tuned on domain-specific datasets spanning six verticals, regulatory texts, financial documents, medical records, real estate contracts, government forms, and legal briefs from the UAE and broader region. Two modes: Reasoning (structured execution plans COGNIS can operationalize) and Generation (human-readable reports, summaries, recommendations). Every decision traceable to data, rules, or context.
Layer 03
COGNIS
The operational core. Receives a user request, understands intent, decomposes it into a directed acyclic graph of sub-tasks, dispatches each to the appropriate skill, monitors execution, handles errors and retries, and assembles the final result, with real-time decisions about ordering, parallel execution, dependency resolution, and resource allocation.
Layer 04
AI Engineering Loops
A continuous five-phase cycle, Evaluate, Learn, Improve, Create, Deploy, operating in the background without downtime. Outputs are scored against quality metrics; corrections become tenant-specific training signal; improvements validate in sandbox before rolling production deploy.
Layer 05
Jarvis
Natural-language chat in English or Arabic. Interprets intent, manages conversation flow, asks clarifying questions, presents intermediate results for approval, and delivers outputs in the requested format. Progressive disclosure: routine tasks with minimal interaction; high-stakes tasks with detailed reasoning and explicit human approval.
Layer 03 · Worked example
Example request
“Process this batch of 500 loan applications, flag high-risk ones, and prepare a summary for the credit committee.”
COGNIS decomposes into 4 parallel pipelines
Supports both synchronous and asynchronous execution. Interactive requests get immediate feedback; batch operations queue, track progress, and notify on completion.
Score outputs against accuracy, relevance, compliance, and satisfaction metrics.
Capture corrections, refine patterns, generate new templates when needed.
Rolling production updates, zero downtime, logged, reversible, audit-traceable.
