Task-specific model router
Optimizes quality, latency, cost, privacy and jurisdiction per task.
Capability layer12 / 12
Model orchestration
No single model is best for every problem. Route each work unit to the expert stack that maximizes quality under cost, privacy and policy constraints.
The right model, specialist agent and review path are selected per task, with confidence, provenance, cost and policy controls attached.
Users receive the best available work product without choosing models, managing prompts or trusting an unexplained black box.
Nmodels, one governed route100%provenance attached0default-model complacency
How it works
From signal
to verified outcome.
- 01
Classify
Resolve task type, jurisdiction, sensitivity, complexity and consequence.
↘ - 02
Route
Select models, tools, expert agents and corpus access for the specific work unit.
↘ - 03
Compare
Use independent candidates, critique and CADE synthesis when stakes justify depth.
↘ - 04
Calibrate
Measure review edits, outcomes, cost and reliability to improve future routing.
↘
System capabilities
Depth beneath
the interface.
CADE ensemble reasoning
Competing expert agents must survive challenge before synthesis.
Confidence & provenance
Every output exposes route, sources, uncertainty and required review.
Review-burden prediction
Estimates human decisions, citation checks and editing time before work begins.
Connected by design
Your systems remain
where work happens.
Apparently adds a permission-aware execution layer across the tools your organization already trusts.OpenAIconnectedAnthropicconnectedGoogleconnectedMicrosoftconnectedPrivate modelsconnectedOn-prem inferenceconnectedCADEconnectedPolicy enginesconnected
Open the system