Dashboard

Evaluation Pipeline

Scoring Matrix

Evaluating: --

Quantum Confidence Score:
--%

Current Evaluation

Awaiting Evaluation
No active evaluation
Business Score (B) --/16
Nature Score (N) --/20
Confidence --%
Total Score --/36

Evaluation Workflow

INPUT
Application Data
Questionnaire
Business Model
Pitch Deck
Layer 0: Quantum Agent
Data Validation
Feature Extraction
Context Enrichment
Gap Identification
Iterative Cycle
Layer 1-2: Quantum ML
QML Classification
QUBO Optimization
Pattern Discovery
Multi-Criteria Scoring
Layer 3: Interpretation
Result Analysis
Reasoning Generation
Convergence Check
Human Handoff
OUTPUT
Probabilistic Scores
Detailed Reasoning
Recommendations
Final Rankings
Assessment Criteria by Round
1
Nature Focus
400+ → 150
Biodiversity Impact Assessment

Assessment of solution's biodiversity impact over the next five years and basic business viability screening.

Nature Criteria
N1 Theory of Change N2 Transformation N3 Condition Change N4 Extent N5 Significance
Business Criteria
B1 Problem-Fit B2 Maturity B3 Team B4 Financial Viability
2
Business Focus
150 → 20
In-Depth Business Analysis

Validate Round 1 assumptions, assess business model impacts, financials, and governance in depth.

Business Deep Dive
Funding Needs Customers Competitive Edge Revenue Model Governance
Nature Enhancement
Negative Impact Adaptability Circularity
3
Jury & Pitch
20 → Winners
Final Selection by I4N Jury

Live pitch presentations assessed on innovation, impact, evidence, and governance. Scale 1-5.

Jury Criteria
Innovation & Adaptability Impact Evidence & Design Purposeful Growth Equitable Governance

Applied Startups

Startup Applications (7 total)
ID Startup Name Country Status Submitted Evaluated Decision Actions
Showing 1-7 of 7 applications
0 selected

Final Select

Module Locked

Quantum-enhanced nomination engine for Round 2 finalist selection. Configure criteria weights, set selection parameters, and let the Quantum system identify the top candidates.

161
Round 2 Pool
39.7% of 406 applicants
21.5
Avg Total Score
B: 10.5 + N: 10.9
82%
For-Profit
132 of 161 candidates
Seed
Top Funding Stage
73 of 161 (45%)

Round 2 Score Distribution

Business Score (B_Sum) avg 10.5 / 16
min 8
Min: 3.0 Median: 10.2 Max: 16.0
Nature Score (N_Sum) avg 10.9 / 20
min 8
Min: 0.0 Median: 11.0 Max: 20.0

Selection Parameters

Configure when unlocked

Selection Engine Locked

The Quantum-enhanced nomination engine will be activated once all evaluations are complete and the selection backend is deployed.

Select how many top candidates the AI should nominate

Adjust the importance of each criterion for the final comparison

B1 Problem-Fit
70%
B2 Maturity
50%
B3 Team
80%
B4 Financial
60%
N1 Theory of Change
90%
N2 Transformation
75%
N3 Condition
85%
N4 Extent
65%
N5 Significance
95%

Additional constraints for the nomination algorithm

Geographic Diversity
Ensure selected finalists represent diverse geographic regions
Sector Balance
Avoid over-representing a single industry sector
Exclude Red-Flagged
Automatically exclude candidates with unresolved red flags
Biodiversity Hotspot Priority
Prioritize startups operating in megadiverse countries or KBAs

This feature will be available once the selection backend is deployed

Nominated Finalists

1
Awaiting selection
2
Awaiting selection
3
Awaiting selection
4
Awaiting selection

Finalist slots will be populated after the Quantum Selection engine processes the Round 2 pool

Export Results

Available after selection
PDF
Nomination Report
Full finalist report with scores, reasoning, and comparative analysis
XLSX
Score Matrix
Spreadsheet with all criteria scores, weights, and ranked comparisons
JSON
API Payload
Machine-readable output for integration with external systems

Q.Engine Evaluation

Evaluate the Quantum Engine against human assessor decisions. Run sample evaluations, compare outcomes, and measure model accuracy with standard ML metrics.

Evaluation Parameters

Percentage of dataset to evaluate

%
~41 cases from 412 total

Which decision category to sample from

Enable Retrieval-Augmented Generation for context-enriched evaluation

RAG Enabled

Quantum Configuration

Module Locked

Fine-tune the Quantum Annealing parameters, configure ML hyperparameters, and customize LLM behavior for optimized evaluation performance.

Transformer Quantum Circuit

32 Qubits Depth 20 PQC Ansatz

Locked

Quantum Annealing

Locked

QML Hyperparameters

Locked

LLM Configuration