AI Agent Orchestration Platform for Governed Multi-Agent Workflows
VDF AI Networks is the multi-agent orchestration platform for governed enterprise AI. Describe a goal — the platform decomposes it, routes it to the right agents and models, executes it with full audit trails, and learns from every run. All on-premise, all EU AI Act-aligned.
Network Builder
Visual drag-and-drop canvas with 14+ node types for any AI workflow
Execution Engine
Real-time orchestration with retry, circuit breaker, and SLO tracking
Full Observability
Cost analytics, energy monitoring, and living knowledge vault
OVERVIEW
From Natural Language to Running Network
Describe your goal in plain language. VDF AI Networks decomposes it into a structured multi-node network, assigns the right agents and tools to each step, and executes the entire workflow — tracking cost, latency, and energy throughout.
Every network is versioned, observable, and improvable. Execution history feeds a living knowledge vault that makes future runs smarter.
- Visual drag-and-drop canvas with 14+ pre-built node types
- LLM-powered task decomposition from a single sentence
- Multi-provider execution: OpenAI, Anthropic, Azure, Ollama, and more
- Per-node cost, latency, token, and energy tracking
- Retry policies, circuit breakers, and fallback routing
- Living knowledge vault with proof of provenance
NETWORK LAB
Visual Network Canvas Builder
Design complex AI workflows without writing orchestration code. The Network Lab gives you a full visual canvas backed by a powerful execution engine.
Task Decomposition
Type a goal in plain language. The LLM decomposes it into a structured network of nodes and connections — no configuration required to get started.
Drag-and-Drop Canvas
Position nodes freely on an infinite canvas. Connect them with sequential, parallel, or conditional edges. Undo/redo support for every change.
Network Templates
Start from pre-built templates for Project Management, Analytics, Support, and more. Customise and save your own templates for reuse across teams.
Network Validation
Built-in validation surfaces configuration errors before execution. Cycle detection, required-field checks, and connection compatibility verified automatically.
Network Versioning
Every saved network creates a version. Compare versions, roll back to previous configurations, and track what changed between deployments.
Duplicate & Branch
Clone any network into a new draft. Experiment with alternative architectures without affecting the live version. Promote branches when ready.
NODE LIBRARY
14+ Node Types for Any AI Workflow
Every node is a composable building block. Combine them to build pipelines from simple chains to complex branching multi-agent systems.
EXECUTION ENGINE
Production-Grade Execution with Full Resilience
Run networks with confidence. Every execution is tracked step-by-step, with automatic recovery from failures.
Step-by-Step Tracking
Every node execution is tracked with individual status (queued, running, success, error, timeout), input/output, token usage, and cost.
Retry & Backoff
Configurable retry policies with linear or exponential backoff per node. Never lose a run to a transient provider timeout.
Circuit Breaker
Automatic provider circuit breaking on repeated failures. Agents route around unhealthy providers without manual intervention.
Fallback Routing
Define fallback targets — a different model, agent, or tool — for any node. Error-specific branching routes failures to dedicated recovery paths.
SLO Tracking
Define service level objectives per network (e.g., p95 latency < 3s). Monitor SLO compliance in real time and receive alerts on breaches.
Execution History
Complete run history with filtering by status, time range, and network. Related run clustering and full provenance proof for every execution.
ANALYTICS
Cost, Energy, and Performance Intelligence
Know exactly what every network costs — in dollars, milliseconds, and kilowatt-hours. VDF AI Networks is the only platform that tracks all three.
Cost Analytics
- Per-execution cost broken down by model, node, and agent
- Daily and monthly cost trends with budget tracking
- Cloud cost comparison: AWS Bedrock, Azure OpenAI, Google Vertex
- Estimated savings vs. running workloads on cloud providers directly
- Optimization recommendations: agent switching, network pausing, load balancing
Energy & Sustainability
- Total energy consumption in kWh per network and per execution
- CO₂ equivalent emissions (grams CO₂e) per run
- Separate prompt (input) and decode (output) energy measurement
- Coverage ratio: percentage of runs with verified energy data
- 7-day energy and CO₂ trend charts
Performance Metrics
- P50 and P95 latency per network and per node
- Token throughput: input, output, and total token counts
- Error rates and failure classification by root cause
- Resource utilization: CPU, GPU, and memory percentages
- Model routing decision rationale and confidence scores
Overview Dashboard
- Mission success rate, active networks, and running executions
- Recent activity feed with status, latency, and cost per run
- Recent agent and model deployment history
- Onboarding progress checklist for new teams
- Cloud vs. VDF platform savings summary
LIVING KNOWLEDGE
Networks That Remember and Get Smarter
Every execution adds to a knowledge vault. VDF AI Networks indexes run artifacts, proofs, and insights — so future executions benefit from everything that came before.
Knowledge Clusters
Groups of related networks are automatically clustered by domain. Navigate your organization's AI knowledge by topic, not just by network name.
Run Artifacts
Every execution generates artifacts — outputs, logs, traces — stored and indexed in the vault. Query them across versions and time ranges.
Proof of Provenance
Every run generates a provenance proof — a verifiable record of which agents, models, and tools produced each output. Compliance teams get a full audit trail.
Knowledge Indexing
Index network knowledge with configurable chunking, overlap, and embedding model selection. Choose scope: single version, all versions, or custom selection.
Learning & Optimization
Model Governance uses a contextual bandit with 5 learning modes to optimize model routing, tool selection, and plan rewriting decisions continuously in production.
Evaluation Suites
Test networks with rubrics and datasets before deploying. Track accuracy scores across versions and receive optimization hints automatically.
Four Implemented Self-Evolving Dimensions (SEEMR)
SEEMR (Self-Evolving Model Router) implements four live dimensions: Model Governance (contextual bandit, 5 learning modes), Agent Personalities, Knowledge Graph, and Cost & Energy Optimisation.
All autonomous. All running continuously in production.
Autonomous RAG restructuring is on the public roadmap.
Zero engineering overhead on the four live dimensions after setup.
GOVERNANCE
Enterprise-Grade Governance and Compliance
PII Redaction Guardrails
Configure per-agent guardrails to redact personally identifiable information from inputs and outputs before they reach any model or storage.
Safety Content Filters
Built-in content safety filters applied at the network level. Configurable severity thresholds with automatic rejection and audit logging.
Tool Allowlists
Define exactly which tools each agent can invoke. Prevent agents from accessing unauthorized systems or data — enforced at the execution layer.
Access Control
Network owners array controls who can view, edit, and run each network. Org-wide and team-scoped permission models supported.
Audit Logging
Full execution traces with input, output, model routing decisions, and rationale. Every run is auditable down to the token level.
Dead-Letter Queue
Failed executions that exhaust retries are routed to a dead-letter sink for manual review, replay, or escalation — nothing is silently dropped.
DEPLOYMENT
Cloud, On-Premises, or Hybrid
VDF AI Networks adapts to your infrastructure requirements. Deploy in the cloud for instant access or on-premises for maximum data sovereignty.
Cloud
Multi-tenant SaaS deployment. Fully managed, zero infrastructure overhead. Connect any cloud AI provider instantly.
- Instant provisioning
- Auto-scaling execution
- Managed monitoring and updates
On-Premises
Self-hosted on your infrastructure. Full data sovereignty, private model endpoints, and integration with internal systems.
- No data leaves your environment
- Private AI provider endpoints
- Custom identity and access management
Hybrid
Cloud orchestration with on-premises model execution. Route sensitive workloads to private infrastructure, general workloads to cloud.
- Per-network routing policy
- Encrypted data in transit
- Unified observability across both
Start Building Your First AI Network Today
Describe a goal. VDF AI Networks decomposes it, routes it, and executes it — with full cost, energy, and performance visibility from the first run.
Related foundational reading
Use these pages to connect the Networks product story to the category architecture behind it.
The category page that explains why orchestration is the missing enterprise layer.
LLM RoutingHow routing balances quality, latency, cost, and energy inside orchestrated workflows.
On-Premise AI Agent PlatformThe broader platform context for enterprises that need controlled deployment.