Knowledge Graph
Neo4j-powered entity relationships and fact storage
- Entity extraction and linking
- Relationship traversal
- Temporal fact versioning
The Orchestration Operating System
Force sits between your agents and production, providing the reliability layer that makes autonomous systems trustworthy. It's not an agent framework—it's operational infrastructure.
How Force Works
Building agents is easy. Making them reliable enough for production is the hard part. The missing layer? Ops and governance.
FORCE provides: state management, recovery, observability, verification—so fleets run reliably across long horizons.
Agent SRE: resumption, replay, and incident response for autonomy
We don't do 'guardrails after the fact.' We do verification before execution.
FORCE is the runtime infrastructure that makes agents reliable.
Agent Architecture
Hierarchical fleet structure with intelligent coordination and delegation
APEX Fleet Coordinator
Squadron A Domain Lead
Squadron B Domain Lead
Squadron C Domain Lead
Team Leads Task Coordination
Workers Execution Layer
Hierarchical Delegation
Work flows from APEX through squadron leads to specialized workers
Parallel Execution
Multiple squadrons and teams execute concurrently for maximum throughput
Dynamic Coordination
Real-time communication and workload balancing across the fleet
Tool System
Model Context Protocol (MCP)
Secure, extensible tool integration through the Model Context Protocol standard.
- Tool Gateway: Centralized routing with permission enforcement
- MCP Integration: Standard protocol for tool discovery and invocation
- Custom Tools: Register domain-specific tools with typed interfaces
- Audit Trail: Complete logging of all tool invocations and results
Memory System
Persistent knowledge graph with semantic search and recall
Vector Embeddings
ChromaDB semantic search across agent memories
- Semantic similarity search
- Hybrid BM25 + vector recall
- Cross-session knowledge
Intelligent Recall
Context-aware memory retrieval and synthesis
- RRF fusion ranking
- Importance decay
- Prospective scheduling
Fleet Orchestration
🌟 APEX Coordinator
Central intelligence that receives objectives, plans execution, and delegates to squadrons. Monitors fleet health and intervenes when needed.
🎯 Squadron Parallelization
Multiple squadrons execute concurrently on different domains. Each squadron manages its own team hierarchy for maximum throughput.
⚙️ Worker Specialization
Leaf workers focus on specific tasks. Skills and domain expertise loaded on-demand. No context pollution between workers.
50+ Concurrent Agents
3 Hierarchy Levels
Real-time Coordination
Core Capabilities
Fleet Orchestration
50+ agents validated in production contexts
- Hierarchical delegation: APEX → Squadron → Team → Worker
- Parallel execution across agent fleets
- Real coordination, not prompt chaining
PULSE Verification
Multi-model consensus verification
- Routes critical decisions through multiple independent models
- Statistical outliers are rejected before propagation
- Catches hallucinations through geometric consensus
Journal + Replay
Complete audit trails for every decision
- Deterministic replay: reproduce any run exactly
- Debugging: what happened, when, and why
- Compliance: proof of work for regulated environments
Durable Execution
Checkpoints and resumption
- Runs survive failures and interruptions
- Resume exactly where you left off
- No lost work, no orphaned state
Technical Specifications
Runtime Rust core (Tokio async)
Messaging Redpanda event bus
Deployment Cloud, on-prem, air-gapped
Scale 50+ concurrent agents validated
Tests 1,251+ passing
Reliability 270M+ fuzz tests executed
See It In Action
Watch Force orchestrate an agent fleet with PULSE verification in real-time.
Live demo running
See It In Action
Experience the orchestration operating system that makes autonomous AI reliable.