The Whitespace Engine
Six weight sliders define your view of what wins. Move one and every vendor's moat recomputes as a normalized weighted sum - the bars reorder, the scatter dots migrate, and the inspector below re-derives the math for the selected vendor, anchored to the cited corpus. Nothing here is a baked rank.
Weights normalize to 100% (share-of-wallet). Drag any axis and the field recomputes live.
The math is a glass box; the inputs are not all fact: 83/162 sub-score cells are analyst-judged. Stress-test them →
Each lens just sets the six weights - proof the ranking is a function of assumptions.
$53M Baird-led growth (Sep 2025) · Agentic Mesh + AI Workbench
| Axis | Sub-score | Weight | Contribution | Provenance |
|---|---|---|---|---|
Agent readiness Ships real multi-step reasoning & agents - not 'agentwash'. | 74 | 22% | 16.3 | synthesis#11 EvoluteIQ product positioning + PrePost GenAI stack-coverage judgment |
Governance & trust Lineage, purpose-based access, masking, policy enforcement. | 70 | 20% | 14.0 | synthesis#11 EvoluteIQ product positioning + PrePost GenAI stack-coverage judgment |
Ecosystem / MCP MCP-native context layer + partner & model gravity. | 58 | 16% | 9.3 | synthesis#11 EvoluteIQ product positioning + PrePost GenAI stack-coverage judgment |
Data gravity Where the data already lives - switching cost & default home. | 48 | 18% | 8.6 | estimate |
Delivery proof Shipped outcomes & logos vs slideware. | 60 | 14% | 8.4 | cited#10 Baird Capital / EvoluteIQ / YourStory / Tech.eu |
Pricing access Mid-market reachability (inverse of enterprise-only lock-in). | 82 | 10% | 8.2 | estimate |
EvoluteIQ's sub-scores are the author's research estimates, scored on the same formula as every other vendor and plotted as a peer dot. Drag the sliders to test how sensitive its ranking is to your assumptions.