Digital Profile
Represents the evolving state of a real-world entity such as a learner, plant, room, workload, or organization.
Advancing the agent-native frontier.
Agentivium AI builds foundational components for agent-native systems: digital profiles, event streams, evidence packets, adaptive actions, policies, and compute-aware orchestration for real-world domains.
Vision
Cross-domain foundations for agent-native systems.
We design agent-native systems around intent, digital state, event streams, evidence, adaptive actions, policy constraints, and resource-aware execution. Agentivium Core defines shared modules; testbeds apply them in real domains and contribute data, schemas, edge cases, and operational knowledge back to the Core.
01Composable Building Blocks
Digital Profile, Digital Stream, Evidence Packet, Adaptive Action, and Evaluation Protocol.
02Evidence-grounded loops
Profiles and actions are updated from traceable event streams and evidence.
03Compute-aware execution
Agents, models, tools, memory, and infrastructure are co-designed for value per compute.
Agentivium Core v0.1
Five shared modules for agent-native systems.
Digital Stream
Records domain events over time so profiles, decisions, and actions can be replayed, queried, and audited.
Evidence Packet
Links claims, insights, and actions to supporting data such as logs, files, sensors, metrics, images, or human notes.
Adaptive Action
Represents actions generated from profile, stream, evidence, and constraints, with results feeding back as new events.
Evaluation Protocol
Measures profile quality, evidence coverage, action relevance, trace completeness, policy compliance, and value-per-compute.
Research Agenda
Four research tracks behind Agentivium Core.
01
Digital Entity Loop
Represent real-world entities as dynamic digital profiles updated by evidence-bearing event streams and acted upon through adaptive actions.
Digital ProfileDigital StreamEvidence Packet
02
Evidence-aware Memory
Memory and knowledgebase mechanisms that select, compress, refresh, and validate information to improve grounding and reduce compute.
Evidence-linked memoryTrace-to-summaryStale memory detection
03
Compute-aware Orchestration
Budgeted execution methods for deciding when to spawn agents, call models, retrieve memory, use tools, retry, stop, or ask humans.
Budgeted agentic executionModel routingAgent scheduling
04
Policy Envelope and Agent-native Evaluation
Policy and evaluation protocols for governing the full lifecycle of agent-native actions, from planning to execution and audit.
Policy EnvelopeHuman approvalTrace completeness
Core-Testbed Flywheel
Testbeds that feed Agentivium Core.
Each testbed applies shared Core modules in a real domain and contributes schemas, taxonomies, datasets, edge cases, and evaluation findings back to the Core.
Agentivium Core
Shared schemas, SDKs, protocols, and design principles for building agent-native systems across domains.
Learner Intelligence Layer
A learning testbed where learner profiles, learning streams, and evidence-based recommendations validate the Digital Entity Loop.
Xanh Narrative Engine
An agriculture testbed that converts plant, product, and farm traces into evidence-grounded narratives.
hpc-claw
An infrastructure testbed for compute-aware orchestration of agentic workloads on HPC systems.
Smart Building PoC
A cyber-physical validation of policy-aware agent-native execution using room, device, and sensor streams.
Agentivium Log
Notes from Agentivium Core and its testbeds.
Testbed Reports
Agentivium AI at HCMUT HPC Summer School 2026: Our First Community Event
HCMUT HPC Summer School 2026 was Agentivium AI's first public academic event - a modest but meaningful step in connecting agent-native systems research with HPC education and community practice.
Announcements
Introducing Agentivium AI
Agentivium AI is a research initiative advancing the agent-native frontier: where autonomous agents become first-class actors in systems, workflows, and society.
Join Us