Product Lifecycle
Every solution follows the same path from lab to production.
Experimental
Active development. Core architecture proven, API surface may change. Available for early adopters and feedback.
Preview
Feature-complete. Hardened through real-world testing. API stabilizing. Available for production pilots.
General Availability
Stable API. Production support. Documentation complete. Ready for enterprise deployment.
Solutions
Swarm
Distributed Multi-Agent Task Orchestration
Submit a natural-language goal and Swarm builds a dependency-aware task plan, discovers your available agents, fans work out across them in parallel waves, and adapts in real time when things go wrong — with graduated recovery from automatic retries through SME consultation to human escalation.
- Six-agent coordination layer: orchestrator, planner, supervisor, workers, blackboard, factory
- DAG-based parallel execution with automatic context propagation
- Zero-registration client agent discovery from live metadata and health state
- Mid-execution replanning when the original plan hits a wall
- Nine configurable termination guards ensure every plan completes
- Full state persistence — resume from host restart without data loss
Knowledge Graph
Hybrid Vector + Graph Semantic Search
A production-grade RAG system that combines vector-based semantic search with SQL Server native graph traversal. Ingest documents, automatically extract typed entities and relationships using LLM-driven pipelines, and retrieve with multi-hop graph traversal — all behind mandatory scope-based access control.
- Four search modes: entity search, chunk search, relationship traversal, and hybrid (vector + graph combined)
- LLM-driven entity extraction with 12 relationship types and 10+ entity categories
- Scope-pinned access control — mandatory on every query, validated at both ends of every edge
- Domain > Category taxonomy with provenance on every result
- SQL Server 2025 native graph tables with VECTOR(1536) embeddings
- Domain intent classification for query-time routing
Long-Term Memory
Three-Temperature Knowledge Persistence
A durable knowledge management system that gives AI agents persistent, structured memory across conversations and sessions. Three temperature tiers — hot (always-loaded index), warm (on-demand LLM-selected recall), and cold (archival vector search) — with intelligent consolidation that merges duplicates, prunes stale observations, and resolves contradictions automatically.
- Hot/warm/cold tiers with bounded token budgets and automatic eviction
- Knowledge graph storage: typed entities (Fact, Rule, Instruction, Observation) with weighted relationships
- Entity matching on save — prevents duplicates by merging similar knowledge with LLM content synthesis
- 4-pass consolidation: deduplication, staleness pruning, contradiction resolution, index truncation
- Synthetic imagining — proactively discovers relevant memories from conversation context
- 3-stage retrieval pipeline: header scan → LLM relevance selection → full content load with graph traversal
Interested in our solutions?
Whether you want early access to an experimental product or need a custom AI solution built on FabrCore, we’d love to hear from you.