/01
Spatial
Intelligence for the physical world
Geography, infrastructure, imagery, records and analytical context align around place. Observed conditions remain distinct from simulated or inferred states.
Explore Spatial →IQAI Systems
Different problems. Different systems.
IQAI develops working systems for physical-world intelligence, investigation, AI evaluation, multi-model analysis and evidence review around a common intelligence architecture. Workflows and deployment readiness remain specific to each system.
Spatial
Connect place, assets, records and observations. Keep simulated conditions distinct from the observed baseline.
Explore Spatial →Choose the question you need to answer.
Start with a place, a relationship, AI behaviour, competing analyses or a document’s evidence. Each system addresses a different question.
/02
Trace
Reconstruct the case. Preserve the evidence.
People, organizations, money, authority, places and events begin fragmented. Evidence-backed relationships become explicit while unsupported possibilities remain visibly unresolved.
Explore Trace →/03
Diagnostics
Evaluate behaviour before relying on it
Repeated outputs are compared across controlled conditions and, where possible, against independently verified references. Confidence and correctness stay separate.
Explore Diagnostics →/04
Advanced Intelligence
Independent perspectives. Reviewable synthesis.
Independent model paths remain separate long enough to preserve disagreement, critique and contribution quality before a synthesis is constructed.
Explore Advanced Intelligence →/05
Risk
Evidence review for AI-assisted documents
Claims are separated from prose and connected to the material that supports them. Weak or unsupported claims remain visibly unresolved for review.
Explore Risk →Common foundation
Working systems. A common architecture.
The systems share recurring needs for evidence, reasoning, explicit checks, specialist methods and human review. Connecting these capabilities into a unified enterprise platform is a development objective. It is not a claim that the integration is already complete.
Current
Working systems
Distinct investigative, analytical and operational workflows.
In development
Platform integration
Connect reusable capabilities around the common architecture.
Objective
Enterprise pilot readiness
Unified, testable, measurable and reviewable deployments.
Readiness and controls must be established for each engagement. Explore Artificial Brain
Explore the nine recurring capabilities
/01IngestionBring differently structured information into a usable workflow.
/02NormalizationCreate consistent structure without erasing source meaning.
/03Identity & relationshipsKeep entities distinct and make material connections explicit.
/04TimePreserve when observations, records, events and decisions apply.
/05Evidence & referenceSeparate source material, support, limitations and independently verified references.
/06Rule-based controlUse calculations, evidence gates, thresholds and policy checks where applicable.
/07AI reasoningUse probabilistic interpretation, classification and synthesis where it adds value.
/08Human reviewKeep consequential judgment and approval explicit.
/09ProvenancePreserve enough of the path to reconstruct how a result became relied on.
These are recurring capabilities, not a claim that every system uses one identical implementation.
The catalogue follows the problems, not the other way around.
The current systems came from specific operating problems. A new requirement may use an existing system, extend one, combine proven capabilities from several areas, or begin as a separate engineering problem.
What matters is whether the problem is consequential, understandable, technically differentiated and capable of producing useful learning.
Choose the problem before choosing the product.
The useful starting point is the operating requirement, the available evidence and what a successful outcome actually needs to support.