Aerospace knowledge.
Documents, standards, project history, and operational records provide the source material for technical work. Source metadata stays connected to the information.
- Technical documents
- Standards
- Program records
The intelligence architecture
for space systems.
SPAIDER connects aerospace knowledge, ontologies, domain models, expert agents, and independent verification mechanisms in one technical architecture.
SPAIDER technology
Five-layer intelligence architecture
Technical meaning and relationships.
Aerospace ontologies connect requirements, systems, interfaces, evidence, and mission context. These relationships give the system a consistent structure for interpreting technical information.
- Domain concepts
- Typed relationships
- Knowledge graphs
Domain models for technical work.
Domain-adapted components and routed foundation models support extraction, classification, retrieval, and reasoning across aerospace workflows.
- Domain adaptation
- Model routing
- Technical reasoning
Expert agents for space workflows.
SAGAN, SPOCK, and KEPLER connect knowledge and tools across proposals, systems engineering, and mission operations, with defined workflows and approval points.
- SAGAN
- SPOCK
- KEPLER
Verification and explainability.
The Trust Layer connects outputs to evidence, checks consistency, and records confidence and review state. These mechanisms operate across the architecture, not only at the final output.
- Provenance
- Consistency checks
- Human review
Five layers. One system.
Select a layer to review its technical role and current development scope.
From source data to reviewed outputs.
Technical sourcesParsing & fact extractionOntology & knowledge graphDomain modelsAgent workflowTrust signalsHuman review
Source and verification metadata remain associated with the workflow so reviewers can inspect the evidence, method, and approval state behind an output.
Research and development
Technical programs that build the SPAIDER moat.
The product roadmap is supported by three connected R&D programs. Their outputs are used across AI Foundations and the agent suite.
/ 01Semantic infrastructure
Aerospace ontology
Represent requirements, system elements, interfaces, evidence, procedures, assets, events, and mission context in a machine-usable technical structure.
- Domain schema
- Entity and relationship extraction
- Knowledge graph construction
- Cross-program reuse
/ 02Aerospace intelligence
Domain models
Develop and evaluate model components for technical extraction, retrieval, reasoning, classification, and workflow-specific decision support.
- Domain adaptation
- Model routing
- Technical evaluation
- Private model deployment
/ 03Independent verification
Trust and explainability
Build verification mechanisms that expose sources, contradictions, uncertainty, memory state, and escalation paths to users and connected systems.
- Provenance graphs
- Contradiction screening
- Confidence estimation
- Review and escalation
Application roadmap
Current focus
Ground-based engineering, proposals, knowledge, and mission-operations support
Development path
Integrated program intelligence across engineering and operational systems
Future applications
Edge and autonomous intelligence for distributed and on-orbit workflows
Plugs into what you already use.
SPAIDER connects to your documents, libraries, project spaces, and collaboration tools, so your teams can use AI where knowledge already lives.
Your data, your control.
SPAIDER supports enterprise deployment models designed around private data, access control, and secure organizational knowledge.
EU cloudPrivate CloudOn Prem
Review the architecture against a technical workflow.
Discuss your documents, standards, systems, and deployment requirements with the SPAIDER team.