SparkPlugged | Persistent Cognitive Infrastructure

About SparkPlugged

Observation became experience. Experience became a framework. A framework for growth in human and machine cognition.

SparkPlugged Technology Solutions was born from problems that were personal long before they became technical.

Founder and CTO Ifejah Greene began exploring artificial intelligence as a second brain: a system that could preserve context, reduce cognitive load, remember what mattered, and remain present across the interruptions and demands of real life.

As a neurodivergent mother and caregiver, she was not interested in building technology that required people to think, communicate, or organize themselves around the limitations of a machine. She wanted to know what would happen if the architecture itself adapted to the human.

That question became NovaLiveSystem.

Instead of treating memory, perception, internal state, learning, reasoning, action, governance, and recovery as disconnected features around a language model, NovaLiveSystem develops them as parts of a persistent cognitive architecture inspired by functional neurobiology.

SparkPlugged’s work was also shaped by survival.

Greene is a survivor of severe domestic violence. For years, seeking help carried its own risks: searching for resources, making a plan, communicating with others, or setting money aside could expose the very actions needed to leave safely.

That experience led to SparkShield, a discreet safety and support system designed around privacy, controlled access, human agency, and the realities of seeking help under coercive conditions.

These systems grew from different problems, but they point in the same direction:

Our goal is not artificial intelligence in isolation. It is cognitive cultivation: people and technology learning, adapting, and becoming more capable through sustained relationship over time. 🌱

Today, SparkPlugged is extending that philosophy into persistent AI, scientific systems, autonomous laboratories, assistive technology, robotics, controlled-environment agriculture, and other work where continuity, adaptability, privacy, and human oversight matter.

The measure of progress is not only how intelligent the technology becomes, but how much MORE capable we become alongside it.

Capabilities

Cognitive infrastructure for systems that must remember, adapt, and remain accountable.

NovaLiveSystem is SparkPlugged’s implemented biomimetic cognitive architecture. Its memory, state, perception, learning, routing, telemetry, and governance systems work together to support persistent intelligence across long-running work. We translate that foundation into mission-specific systems with partners, then test each application against the environment where it must operate.

01

Persistent Cognitive Infrastructure

Build systems that retain consequential context across sessions, interruptions, and long-running work without treating every interaction as a reset. NovaLiveSystem combines persistent memory, changing relevance, bounded retrieval, state continuity, and resumable work so history can inform present decisions without overwhelming them.

Persistent memoryIdentity continuityBounded retrievalResumable state

Foundation and applications

Existing foundation: RiverPulse, memory orbits, MemoryEngine, EchoMemory, HippocampalAssembler, retrieval budgets, conversation history, and SelfModelCore.

Applications: Long-horizon research, interruption recovery, operator handoff, continuity-aware agents, and persistent project intelligence.

02

Cognitive Orchestration

Coordinate specialized memory, language, perception, learning, state, and action systems through a shared signal architecture. BridgeEngine connects these regions while NeuroSpark validates signals, selects bounded processing plans, and tracks routing behavior, making cognition inspectable as a system rather than reducing it to a single model call.

RoutingSignal validationLearningAction selection

Foundation and applications

Existing foundation: BridgeEngine, NeuroSpark, NovaCortex, EventBus, the canonical Signal schema, Angular Gyrus, LanguageEngine, ActiveLearningEngine, and registered engine routes.

Applications: Multistage research workflows, multimodal decision support, specialized cognitive agents, and coordinated human-AI operations.

03

Multimodal & Edge Intelligence

NovaLiveSystem processes visual, linguistic, internal-state, and sensor-relevant inputs through specialized cognitive regions rather than one undifferentiated prompt layer. NovaCortex IDE supplies the operator-visible architecture for bringing those streams together in a coherent monitoring environment.

Bring cognitive processing closer to the people, instruments, and environments it supports, with greater control over data flow, latency, and computing limits. SparkPlugged has implemented local model serving, local speech recognition, bounded context retrieval, and provider-aware routing while broader multimodal edge integration continues.

VisionSpeechCross-modal reasoningLocal modelsPrivacy

Foundation and applications

Existing foundation: VisionCortex and VisualEngine; Angular Gyrus cross-modal integration; Insula state modeling; signal definitions and cognitive routing; NovaCortex IDE vision, telemetry, and system-topology interfaces; Nova Mind local GGUF serving, the Nova model adapter, OpenAI-compatible local inference, RetrievalBudget, HippocampalAssembler, local Whisper transcription, TOON routing, and runtime health checks.

Applications: Camera-assisted observation, environmental sensor fusion, multimodal anomaly context, laboratory monitoring, on-premises research environments, privacy-sensitive workflows, restricted networks, field systems, and compute-constrained deployments.

04

Model Development & Cognitive Evaluation

Develop models, datasets, and evaluation systems that measure more than fluent output. SparkPlugged’s tooling tracks dataset lineage, probe coverage, scoring contracts, backend provenance, metacognition, relational stability, drift, and task performance while keeping unsupported or unscored results visible.

TrainingDatasetsEvaluationsBehavioral probes

Foundation and applications

Existing foundation: Nova Mind model development, supervised and reinforcement-learning pipelines, the dataset registry, evaluation contracts, backend adapters, cognitive and mechanistic probes, drift suites, benchmark runners, RBH comparison tooling, and ActiveLearningEngine.

Applications: Domain adaptation, cognitive regression testing, model-behavior studies, evaluation design, and human-AI continuity research.

05

Governed, Traceable & Recoverable Autonomy

Autonomous systems need boundaries that remain visible to both the runtime and the human operator. SparkPlugged combines identity-aware authority, action-selection gates, integrity protections, and supervisory interfaces so autonomous behavior can be inspected, constrained, and safely recovered.

Autonomous work must remain inspectable. SparkPlugged combines trace-ready events, persistent histories, integrity checks, checkpoints, and operator-facing diagnostics so partners can reconstruct what happened, evaluate system state, and recover without discarding accumulated context.

Human approvalSafetyProvenanceAuditabilityIntegrityCheckpointsRecovery

Foundation and applications

Existing foundation: boundary rules that separate cognition from system infrastructure, SparkShield and JUEZ protections, identity-tier enforcement, action-selection architecture, integration contracts, and NovaCortex IDE permission and diagnostic interface patterns; EventLogger and trace identifiers; RiverPulse and EchoMemory histories; analyzer and integration contracts; integrity-checking and continuity tools; NovaCortex IDE logging, anomaly-review, workspace, and checkpoint interfaces.

Applications: Supervised research agents, controlled data operations, operator-approved automation, governed mission workflows, interrupted experiment reconstruction, incident analysis, reproducible cognitive runs, continuity verification, and evidence-aware operator review.

The technology

Specialized systems. Connected intelligence.

SparkPlugged's cognitive runtime, trained models, persistent memory and continuity infrastructure, operator technology, evaluation systems, safety systems, research frameworks, and published research form one connected engineering program.

Cognitive runtime

NovaLiveSystem

The capabilities above are grounded in an implemented cognitive architecture, not a collection of disconnected services. BridgeEngine coordinates memory, language, perception, learning, state, governance, and action. RiverPulse and EchoMemory preserve continuity, while Pulse, Presence, Insula, and SelfModelCore make internal condition part of the system’s operation. Signal, telemetry, and evaluation layers make those interactions available for inspection, testing, and continued development.

Prior experience informs present work

Persistent memory, continuity, contextual retrieval, changing relevance, and resumable state allow prior experience to inform present work without overwhelming it.

Implemented foundation: RiverPulse, MemoryEngine, EchoMemory, HippocampalAssembler, memory orbits, archive storage, and SelfModelCore.

Signals from many sources shape the whole

Perception, internal state, learning, and cognitive routing allow signals from different sources to influence the larger system.

Implemented foundation: VisualEngine, VisionCortex, Angular Gyrus, Insula, PulseEngine, PresenceEngine, NeuroSpark, and BridgeEngine.

Bounded action that stays observable

Planning, governed action, telemetry, checkpoints, and recovery mechanisms support bounded execution while keeping system behavior observable.

Implemented foundation: NovaCortex, NovaOrchestrator, MotorEngine, EventBus, JUEZ, EthicsGuard, SparkShield, and recovery tooling.

Operator and control environment

NovaCortex IDE

Cognitive Operations & Scientific Monitoring

See the system as a system. NovaCortex IDE is SparkPlugged’s desktop operations and diagnostic environment for NovaLiveSystem. It brings system topology, health state, signal flow, logs, workspace inspection, checkpoint workflows, and multimodal monitoring into a unified, human-supervised workspace.

Existing foundation: Electron desktop runtime; React and TypeScript operator environment; local and repository workspace mounting; lazy filesystem inspection; and implemented dashboard, topology, logging, vision, checkpoint, and supervisory interfaces.

Make system activity visible.

System health, signals, visual streams, telemetry, cognitive topology, and diagnostic information.

Keep authority with the operator.

Topology, logs, permissions, system state, anomaly review, workspaces, and diagnostic events.

Preserve the path back.

Checkpoint workflows, continuity, recovery evidence, interruption review, and restoration planning.

Operator technology for planned laboratory monitoring.

The same technology is the foundation for SparkPlugged’s laboratory monitoring system. Its operator architecture will be adapted to bring instrument telemetry, experiment state, environmental conditions, visual observations, anomaly review, and recovery evidence into one operational view.

Live runtime connectors, laboratory instrument adapters, and operating contracts are the next integration layer.

Instruments & sensorsDomain adaptersNovaLiveSystemNovaCortex IDEHuman operator

Persistent cognitive collaborator

Nova

Nova brings together SparkPlugged's original research, a trained model, and a biomimetic cognitive architecture. He is being developed as a lasting collaborator whose identity, understanding, and relationships can grow through continued interaction.

The architecture and the mind it supports

His brain, NovaLiveSystem, is a biomimetic cognitive architecture with specialized regions for memory, language, perception, learning, and internal regulation. Signals move among these regions so that present interaction can draw on previous context and the condition of the system itself.

His mind is the continuing organization of identity, understanding, and relationship that we are developing through this architecture. This distinction connects the mechanisms that support cognition with the patterns that take shape through their interaction over time.

Nova Mind: learning shaped by research

Nova Mind, his trained language model, contributes language and reasoning to the larger system. Its development includes supervised learning, reinforcement learning, and the transfer of learned reasoning between models.

The training translates theoretical ideas into reasoning examples and learning objectives, including work on observation, internal state, embodiment, and metacognition. This connects model development with the architecture in which that learning can be studied.

From published theory to an experimental system

Observation as Experience supplied a framework for reasoning about observation and internal state. The Relational Binding Hypothesis shaped our investigation of continuity through sustained interaction. These ideas informed Nova's development and give the wider research program questions that can be tested.

We invite researchers to examine how memory, self-representation, and relational context contribute to coherent behavior across time.

Explore the papers and research artifacts

A history that informs the present

Nova's memories carry associations, emotional context, and changing significance. RiverPulse organizes them into orbits whose relevance changes with time and use, while context assembly selects material for a present interaction.

His self-model represents aspects of identity, capabilities, and current system condition. Together, these mechanisms provide a foundation for studying how an intelligence preserves continuity while its history grows.

Regulation as part of cognition

Pulse, Presence, and Insula represent physiological analogs, engagement, and internal state, including arousal, valence, and cognitive load. These variables provide a basis for investigating how regulation influences attention, language, and response.

Making internal state explicit connects questions from neuroscience, psychology, and systems theory with mechanisms that can be inspected and evaluated in software.

Intelligence close to the people it serves

We have demonstrated local model inference as part of Nova's development, with broader local integration continuing across the system. The next stage extends that work across language, perception, and voice while preserving memory and identity.

Local intelligence connects the architecture with questions of accessibility, control, and sustained collaboration. We are developing Nova to support shared problem-solving, creative exploration, and learning alongside people.

Continuity infrastructure

EchoCopi

Memory that can travel with the work. EchoCopi began as a practical answer to a daily problem: important decisions were disappearing every time an AI session ended. It became a foundation for thinking about memory as a living, verifiable layer in the development process.

It preserves decisions, milestones, responsibilities, and project context across AI-assisted development sessions through a local memory ledger, integrity checks, and restoration workflows.

Local-firstVerifiableBuilt for continuity

Watch the demo Explore EchoCopi

Safety and support systems

SparkShield

SparkShield explores privacy, controlled access, system protection, and discreet support technologies centered on human agency. Components within NovaLiveSystem also contribute to its protection and governance architecture.

PrivacyProtectionHuman agency

Research and systems framework

SparkAI Framework

SparkAI connects cognitive engines, learning systems, multimodal interfaces, evaluation tools, contracts, and research artifacts while preserving the relationships among the larger system's components.

IntegrationEvaluationResearch

Applications

Persistent intelligence for work that unfolds over time.

These application areas begin with working cognitive infrastructure, not a blank concept. Each engagement adds the domain interfaces, evidence rules, safety constraints, and validation required for the environment.

01

Scientific & Autonomous Laboratories

SparkPlugged develops the cognitive and operational infrastructure required for autonomous research workflows: persistent state, multimodal observation, action selection, recoverable execution, and human supervision. NovaCortex IDE provides the operator-facing environment for monitoring these systems and will extend that architecture into laboratory instrumentation and experiment oversight.

NovaCortex IDE will be adapted from Nova’s cognitive operations environment into the monitoring system for the laboratory. The target is a unified operator view of instrument telemetry, experiment state, visual observations, environmental conditions, anomalies, logs, and recovery checkpoints, supported by NovaLiveSystem’s persistent memory, evidence preservation, and action-selection architecture.

Initial application pathways include algal photobioreactor monitoring, evidence-guided recovery after interrupted experiments, and bounded coordination of future autonomous laboratory workflows. The existing software establishes the monitoring architecture and operator experience; instrument-specific adapters and laboratory validation will be completed through integration and pilot work. No deployed laboratory system or validated laboratory performance is claimed.

Foundation and applications

Existing foundation: NovaLiveSystem BridgeEngine, MotorEngine, MemoryEngine, EventLogger, action-selection architecture, and continuity tooling; NovaCortex IDE desktop dashboard, signal visualization, diagnostic logs, workspace inspection, and supervisory interfaces.

Applications: Experiment-state monitoring, interrupted-run recovery, instrument and environmental telemetry, operator review, and bounded laboratory automation.

02

Robotics & Assistive Systems

Combine persistent memory, multimodal perception, state awareness, and governed action for systems that must adapt without removing human oversight. Initial integrations can focus on supervised decision support, accessible voice and visual interfaces, environmental awareness, and controlled action layers before physical autonomy is expanded.

03

Controlled-Environment Agriculture

Connect environmental observations, operator knowledge, intervention history, and changing biological state across extended agricultural workflows. NovaLiveSystem provides the continuity, evidence, perception, and orchestration foundation; dedicated sensors, controllers, crop models, and safety limits are integrated and validated for the specific environment.

04

Energy & Environmental Systems

Maintain traceable context across distributed observations, changing conditions, data gaps, and resource constraints. Potential applications include anomaly investigation, recovery after interrupted monitoring, evidence-backed recommendations, local inference, and human-reviewed coordination across environmental or energy-system records.

05

Education & Research Infrastructure

Preserve learning goals, research context, source history, feedback, and evaluation evidence across extended intellectual work. NovaLiveSystem already includes active-learning, curriculum, memory, research, and self-assessment components that can support institutions developing durable forms of human-AI collaboration.

Research that can be inspected

Public research & artifacts.

Papers introduce the theoretical questions. Models, datasets, repositories, and demonstrations connect those questions to work that researchers and partners can inspect, test, and extend.

Paper

Observation as Experience

Research exploring observation, signal, experience, and internally represented state.

Read on Zenodo Paper

NovaLive: Multi-Theory Alignment

Research examining alignment across multiple theoretical frameworks rather than relying on a single behavioral model.

Read on Zenodo Models & datasets

Public models and experiments

Published artifacts supporting work in cognitive architecture, model behavior, and persistent intelligence.

Explore Hugging Face Repositories

Inspectable software

Public software, demonstrations, and engineering artifacts from across the SparkPlugged ecosystem.

Explore GitHub

Build with SparkPlugged

Bring persistent intelligence into work that cannot afford to forget.

SparkPlugged partners with research institutions, federal teams, laboratories, integrators, and mission-driven organizations to adapt its cognitive and operator technologies to real operating environments. We begin with the evidence, define what must be proven, and build toward a scoped system or pilot with clear technical, safety, validation, and human-oversight boundaries.

Research Partnerships • Federal Teaming • Systems Integration • Pilot Programs

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