Platform

Structured intelligence infrastructure.

PRISM is a configurable data and intelligence platform. Collection is an intake mechanism. The product is the path from fragmented information to governed, usable intelligence.

Collection → Structure → Governance → Integration → Analytics → AI → Decision support

Structured data collection

  • Configurable forms and workflows
  • Progressive disclosure
  • Conditional fields and branching
  • Standardized data schemas
  • Longitudinal collection
  • Mobile-friendly interfaces

Data governance

  • Data compartmentalization
  • Identity separation
  • Deidentified and pseudonymized datasets
  • Role-based access
  • Auditability
  • Configurable retention
  • Research and operational separation

Integration layer

  • REST APIs
  • Structured exports
  • External system integration
  • Research system integration
  • Dashboard integrations
  • Future enterprise interoperability

Business intelligence

  • Dashboards
  • Trend analysis
  • Longitudinal analysis
  • Population-level insights
  • Resource allocation support
  • Operational decision support

AI harness

The value is not tied to a vendor.

PRISM prepares high-quality, structured, governed data and provides a controlled interface through which AI and analytics services can operate.

  1. 01

    Fragmented data

    Forms, notes, operational records

  2. 02

    PRISM data layer

    Schemas, workflows, longitudinal records

  3. 03

    Governance

    Permissions, quality, identity separation

  4. 04

    AI harness

    Standard request and response interface

  5. 05

    Interchangeable models

    Model A · Model B · Model C · Analytics

  6. 06

    Actionable intelligence

    Research · trends · decisions · BI

PRISM transforms fragmented information into governed, AI-ready data while remaining model agnostic by design.

Models can change without changing the collection workflow, database schema, customer experience, or core platform. Potential providers include commercial APIs, government-hosted services such as Amazon Bedrock, open-source models, or locally deployed inference — selected by mission, security, cost, and hosting constraints.

Demonstrated prototype capabilities today include structured extraction and advisory text assistance behind an internal adapter. Broader pattern detection, hypothesis generation, and multi-model evaluation are intended architecture, not claimed production features.