Technical Data Sheets

Comprehensive technical specifications and capabilities of ANDI's intelligent data platform

Product Roadmap & Capabilities

In Development
Q2 2025

MVP - Foundation Intelligence

Core capabilities for intelligent data analysis

NLP Query Engine

Ask questions in plain language and receive structured insights

Technical Requirements

  • LLM/NLP model hosting
  • Natural language parser
  • Query translator
  • Analytics layer integration
LinkDNA™ Correlation Engine

Links records without shared IDs using synthetic identifiers

Technical Requirements

  • Data normalization services
  • Fuzzy matching algorithms
  • Record scoring engine
  • Confidence-based decisions
Insight Labeling

Automatically tags findings by business impact

Technical Requirements

  • Impact taxonomy model
  • Tagging engine
  • Insight classifier service
  • Business impact scoring
Confidence-Based Output

Every insight delivered with confidence score and reasoning

Technical Requirements

  • Explainability engine
  • Scoring model
  • Logic trace framework
  • Transparency reporting
Multi-Dataset Analysis

Correlates siloed data sources across departments

Technical Requirements

  • Multi-source ingestion
  • Schema-mapping module
  • Cross-dataset joins
  • Data correlation engine
Single-User Workspace

Clean, solo-user interface for testing and insights

Technical Requirements

  • Basic user auth
  • UI interface
  • User storage
  • Query state management

Platform Infrastructure

Data Source Tracker

Monitor connection status and sync performance

  • Sync monitor service
  • Pipeline health logs
  • Integration dashboard
Customizable Dashboards

Resize, reshape, and rearrange dashboard widgets

  • Widget layout engine
  • Drag-and-drop UI
  • Layout persistence
Feedback Loop Engine

Captures user feedback to improve matching logic

  • Feedback collection
  • Learning database
  • Retraining hooks
Enterprise Security

AES-256 + TLS 1.3 encryption with audit logs

  • Data encryption
  • Immutable logs
  • RBAC
  • PII masking

Deployment Options

Cloud Deployment

Fully managed SaaS solution

  • Auto-scaling
  • 99.9% uptime SLA
  • Global CDN
  • Automatic updates
On-Premises

Complete control and data sovereignty

  • Air-gapped deployment
  • Custom security policies
  • Local data residency
  • Dedicated support
Hybrid

Best of both worlds

  • Flexible data placement
  • Burst to cloud
  • Edge processing
  • Unified management

Success Metrics & KPIs

85%+

Match confidence in correlation engine

90%+

Clarity score in user feedback

<5s

Insight delivery time for basic queries

3+

Siloed datasets ingested and linked