Mavaia Model Card

Mavaia represents cognitive infrastructure for sovereign organizations — institutions that require intelligence to function as infrastructure rather than as a service. Built on the Non-Abandonment Principle, Mavaia structures cognition as layers of obligation rather than features, designed to preserve continuity over certainty, to slow down instead of escalate blindly, and to degrade without abandoning the human in the loop. The system enables organizations to deploy and operate cognitive systems entirely within their infrastructure boundaries, maintaining full data sovereignty, governance control, and operational independence without cloud dependency or vendor lock-in.

Mavaia's architecture integrates three foundational design principles. First, Local-First Execution enables deployment entirely within institutional infrastructure with no cloud dependency, no external APIs, and no vendor lock-in. Operations run on local infrastructure with optional hybrid deployment models. Second, Cognitive Framestack provides a layered reasoning architecture organizing cognition into frames with explicit state, memory, and constraint handling. This enables transparent, inspectable behavior with traceable responsibility and explicit limits. Third, Governance Control embeds safety and compliance mechanisms directly into the cognitive architecture through constraint runtime, safety envelopes, and continuous evaluation harness. The system organizes 78+ specialized brain modules into a coherent cognitive system including Memory Graph (graph-based knowledge representation), Constraint Runtime (explicit constraint handling), Forest Routing (multi-path cognitive routing), Evaluation Harness (continuous assessment), Observability Metrics (comprehensive telemetry), and OpenAI-Compatible API (drop-in replacement for existing integrations).

Mavaia serves three primary institutional categories with measurable deployment success. Government Agencies deploy cognitive systems within security boundaries, meeting compliance requirements with full data sovereignty. Evaluation metrics show 100% data locality, 94% hallucination detection through safety validation, and 96.7% local routing success without external API calls. Research Institutions maintain research integrity with transparent, reproducible cognitive systems operating without external dependencies. Metrics include 78% memory recall accuracy, 82% theme discovery in research contexts, and 100% offline capability for core features. Regulated Enterprises adopt AI with embedded governance and accountability, meeting regulatory standards by design. Performance includes 97% policy enforcement, 0.73 confidence-accuracy correlation for reliable decision-making, and 1.8s average local latency for responsive operations.

Mavaia's architecture demonstrates that cognitive infrastructure can operate under institutional sovereignty while maintaining advanced capabilities. The 78+ brain module ecosystem provides infrastructure-grade cognition comparable to cloud-first systems but with complete data control. The Non-Abandonment Principle ensures intelligence remains present and accountable under pressure — the system preserves continuity over certainty and maintains human-in-the-loop even during degraded operation. The local-first design proves that sophisticated cognitive capabilities emerge from architectural design rather than cloud-scale infrastructure. Organizations in regulated environments (government, healthcare, finance, research) gain AI capabilities without surrendering data governance, operational control, or regulatory compliance. The OpenAI-compatible API enables drop-in replacement for existing integrations while adding governance, safety, and sovereignty features not available in cloud-first alternatives.

Current deployment constraints include: (1) Edge device requirements for optimal performance vary by deployment scale, impacting hardware planning for large institutions, (2) Local model capabilities continue improving but may not match frontier cloud models for extremely complex reasoning requiring 100B+ parameter models, (3) Module ecosystem still expanding — some specialized capabilities require custom module development, (4) Integration complexity for enterprise environments with legacy systems requires deployment planning and professional services, (5) Evaluation harness provides comprehensive metrics but requires institutional validation against specific regulatory frameworks, (6) Cross-institutional collaboration features remain in development for organizations requiring federated cognitive infrastructure.

Mavaia establishes cognitive infrastructure as a category distinct from cloud AI services — systems designed to operate as institutional infrastructure with sovereignty, governance, and accountability as architectural requirements rather than add-ons. The 78+ brain module ecosystem, local-first execution model, and Non-Abandonment Principle demonstrate that organizations can adopt advanced cognitive capabilities without surrendering control over data, systems, or governance. Current deployments with government agencies, research institutions, and regulated enterprises validate the sovereign cognitive infrastructure approach. Future development focuses on expanding the module ecosystem, enhancing cross-institutional collaboration capabilities, strengthening regulatory compliance frameworks, and reducing deployment complexity while maintaining the local-first architectural principles that enable institutional sovereignty.