AI model configurations for structured market research
iPulse uses model configurations as part of a broader research architecture. The value is not only the model, but the combination of analyst persona, execution mode, task instructions, output schema, and consensus packaging.
Persona
The analytical identity and investing lens.
Mode
The execution style, depth, and capability layer.
Model
The underlying language model configuration and version lineage.
Research architecture
Why this matters for investors
These pages explain the public-facing logic behind iPulse so visitors can understand the product before signing up.
Models are one layer of the system
A model specification defines the underlying generation capability, but iPulse wraps that capability in domain-specific analyst personas, forecast tasks, validation, and structured output formats.
Versioning supports comparability
Model versions and task versions matter because forecast outputs need lineage. iPulse is designed so outputs can be traced to the analyst, task, model, and prompt architecture used to generate them.
The product focuses on comparison
One model answer is fragile. A structured comparison of analyst outputs is more useful for understanding uncertainty, disagreement, and scenario sensitivity.