API Documentation

 

DecisioQ API 1.0 (Coding Examples)


The DecisioQ API is a real-time decision intelligence platform that helps software applications evaluate alternatives, apply business rules, rank options, and generate explainable recommendations.

Modern applications frequently need to answer questions such as:

  • Which supplier should we select?
  • Which vehicle should be purchased?
  • Which claim should be prioritized?
  • Which carrier provides the best value?
  • Which customer application should be approved?
  • Which inventory item should be replenished first?

While these decisions appear straightforward, they often involve multiple competing criteria including cost, risk, quality, performance, compliance, availability, sustainability, and customer satisfaction.

The DecisioQ API provides a web-based decision engine that enables developers to submit structured decision data and receive a ranked list of alternatives, a recommended option, confidence metrics, and a detailed explanation of how the recommendation was derived.

By externalizing decision logic into a dedicated API, organizations can implement consistent, transparent, and auditable decision-making across multiple applications without maintaining custom scoring algorithms in every system.

Decision Intelligence Technology

Decision intelligence combines mathematical optimization, multi-criteria decision analysis (MCDA), business rules, and explainable AI techniques to support complex operational decisions.

The DecisioQ engine evaluates alternatives through a multi-stage decision pipeline:

  1. Input validation
  2. Criteria normalization
  3. Weight generation or validation
  4. Constraint evaluation
  5. Alternative scoring
  6. Ranking generation
  7. Recommendation selection
  8. Confidence analysis
  9. Explanation generation
  10. Sensitivity analysis (optional)

The result is a transparent decision process that allows users and developers to understand not only which option was selected, but why it was selected.

Unlike traditional scoring systems that rely on a single formula, DecisioQ supports multiple decision methodologies including:

  • TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)
  • Weighted Scoring Models
  • Analytical Hierarchy Process (AHP)
  • Rule-Based Constraints
  • Scenario Analysis
  • Sensitivity Analysis

Explainable Decisions

One of the most important aspects of enterprise decision systems is explainability.

Applications consuming the DecisioQ API receive:

  • Final recommendation
  • Ranked alternatives
  • Confidence score
  • Decision rationale
  • Weight distribution
  • Constraint violations
  • Decision trace information

This information can be displayed directly to end users, auditors, analysts, managers, or automated systems.

The explainability framework enables organizations to demonstrate how decisions were made and helps identify potential bias or unexpected outcomes.

Common Use Cases

Automotive

  • Vehicle acquisition
  • Fleet replacement planning
  • Dealer inventory optimization
  • Trade-in evaluation
  • Transportation provider selection
  • Auction strategy optimization

Logistics

  • Carrier selection
  • Route prioritization
  • Warehouse evaluation
  • Shipment scheduling
  • Vendor comparison

Auto Insurance

  • Claim prioritization
  • Fraud investigation ranking
  • Repair facility selection
  • Risk assessment

Fleet Management

  • Vehicle replacement analysis
  • Maintenance prioritization
  • Sustainability initiatives
  • Driver allocation

Leasing and Rental

  • Customer approval workflows
  • Vehicle allocation
  • Remarketing decisions
  • Dynamic pricing analysis

Parts and Supply Chain

  • Supplier selection
  • Inventory replenishment
  • Distribution planning
  • Procurement optimization

RESTful API Architecture

The DecisioQ API follows REST architectural principles.

All requests are sent using HTTPS and responses are returned in JSON format.

Base URL

https://api.decisioq.com/v1

Authentication

All API requests require an API key.

Example:

Authorization: Bearer YOUR_API_KEY

Applications should securely store API credentials and never expose keys within client-side applications.

API Endpoints

The current API includes the following endpoints:

  • GET /health — returns API status and version
  • GET /api/templates — returns available decision templates
  • POST /api/decide — runs a full decision evaluation
  • POST /api/ahp/generate — generates criterion weights from pairwise comparisons
  • POST /api/decision/sensitivity — analyzes how stable a decision is when criteria change
  • POST /api/decision/scenario — compares a base decision against a modified scenario

Decision Evaluation

Runs a complete decision analysis.

POST /api/decide

This endpoint accepts a decision model containing alternatives, criteria, constraints, and configuration settings.

The response contains:

  • Recommended option
  • Ranked alternatives
  • Confidence score
  • Explanation
  • Decision trace

AHP Weight Generation

Generates decision criteria weights using the Analytical Hierarchy Process.

POST /api/ahp/generate

This endpoint is useful when business stakeholders can compare criteria relative to one another but cannot easily assign numeric weights.

Sensitivity Analysis

Evaluates decision stability when criteria weights change.

POST /api/decision/sensitivity

Sensitivity analysis helps determine whether the recommended option remains optimal under changing business priorities.

Scenario Analysis

Compares alternative decision scenarios.

POST /api/decision/scenario

This endpoint allows applications to test hypothetical situations and compare outcomes against a baseline decision.

HTTP Status Codes

The DecisioQ API returns standard HTTP status codes.

Status Code Description
200 Successful request
400 Invalid request
401 Unauthorized
403 Forbidden
404 Resource not found
429 Rate limit exceeded
500 Internal server error

Best Practices

To maximize decision quality:

  • Provide complete and accurate alternative data.
  • Use normalized criteria whenever possible.
  • Define realistic business constraints.
  • Periodically review criteria weights.
  • Use sensitivity analysis for high-impact decisions.
  • Store decision traces for audit and compliance purposes.
  • Monitor confidence scores when automating critical decisions.

By following these practices, applications can leverage DecisioQ as a reliable, transparent, and scalable decision intelligence platform.