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Xenera
An engineered network of autonomous agents — composable, auditable, and self-reinforcing.
Build, orchestrate, and scale intelligence across a decentralized compute fabric, where every contribution is verifiable and every agent strengthens the whole.
Composable Agentsmodular intelligence flows
Distributed Computeelastic GPU capacity
On-chain Attributionverified contributions
Collective intelligence, engineered for scale
Xenera fuses composable agents, verifiable contribution primitives, and a distributed compute fabric into a single operating layer. Agents are modular: they connect, orchestrate and self-optimize across pipelines — while every contribution stays auditable and rewardable.
1,024
Active Agents
2.8K
Verified Nodes
4.7M
Cycles / day
Orchestrator
pipeline conductor
Insight
analytics agent
Verifier
on-chain auditor
Compute
GPU fabric
Flow
data router
Monitor
health & latency
Composed
Edge node
Passive / Archive
How Xenera Actually Works
A concise flow: discover agents, compose pipelines, deploy to the compute fabric, monitor results, and earn for contributions.
Compose Pipelines
Drag, chain, and parametrize agents into reliable pipelines. Reuse modules, version your stacks, and run locally or in-network.
Deploy to Fabric
Dispatch pipelines to the distributed GPU fabric or to edge nodes. Choose latency, cost, and replication policies per job.
Observe & Optimize
Realtime metrics, provenance traces, and drift detection give you visibility. Retrain, recompose, or reroute with one click.
Reward & Govern
Contributions are recorded on-chain. Earn rewards for compute, data, and agent improvements; vote on evolution with XNR.
Built for transparency and composability — every step is auditable, versioned, and permissioned by your policies.
Frequently asked questions
Short answers for teams and builders. Still want more detail? Visit the docs or open a ticket in community.
Xenera is a composable, protocol-backed network of autonomous AI agents. Builders, data custodians, infrastructure providers, and product teams use Xenera to compose agent pipelines, run workloads on a distributed GPU fabric, and capture verifiable provenance and rewards for contributions.
Agents are modular units with explicit inputs, outputs, and metadata. You compose agents into pipelines using the Agent Builder, snapshot versions for reproducibility, and publish manifests that include dependency graphs and provenance traces.
Privacy is layered: job-level isolation, encrypted transport, and configurable execution policies. Sensitive data can be kept on-premise or processed at trusted edge nodes; only distilled, auditable fingerprints or metadata are recorded on-chain unless you opt in.
XNR is the protocol token for access, staking, and rewards. When your node, dataset, or agent contributes value (compute done, model improvements, useful data), that activity is recorded and eligible for rewards according to configurable reward curves and governance policies.
Yes. Deployments accept policy profiles: latency-optimized (edge first), cost-optimized (spot fabric), or highly replicated (multi-region). Profiles determine node selection, redundancy, and price estimation before you commit a job.
Governance is token-driven with off-chain signal and on-chain execution paths. XNR holders vote on parameter updates, reward schedules, and module approvals. Critical upgrades require multi-stage review to protect the network.
Xenera ships SDKs for JavaScript/TypeScript, Python, and a CLI for deployment and monitoring. Connectors exist for common data stores and observability platforms. Third-party integrations can be published to the registry.
Create an account, install the SDK or CLI, and bootstrap a sample agent from the template library. Publish a v1 manifest to the registry, then run test deployments on the dev fabric. Developer documentation and quickstarts live in Docs → Developer.
Live Market Overview
Real-time liquidity, volume, and price movement for XNR — powered directly by DexScreener.
Stay updated with the latest market signals. Track momentum, liquidity, and agent-layer activity across the network.
