Total ISVs
247
Active in pipeline
↑ +18 this month
Tier 1
42
High-value ISVs
↑ +3 upgraded
Allocated
$86.4M
of $100M budget
86.4% deployed
Avg Final Score
63.7
Portfolio-wide
↑ +2.1 vs last cycle
Model Agreement
78%
Manager vs model
↑ +4pts
ISV Portfolio
Click any row to open detail drawer
| Company | Segment | Final Score ↓ | Tier | Confidence | Bucket | Budget Rec. | Status |
|---|
Showing 8 of 8 ISVs
Tier Distribution
Budget Buckets
$70M
Exploit
70% of total
$20M
Explore
20% of total
$10M
Strategic
10% / Manual
Score Distribution
Segment Breakdown
Evaluation Metrics
Tier Accuracy78%
Investment Precision72%
Top-10% Hit Rate84%
Pending Reviews4
AI Label Coverage100%
Live Score Calculator
Adjust inputs — all scores recompute instantly
A · ML Score (base)
ML Score72
B · Strategic Alignment
Azure Native80
AI Usage85
Data Stack70
Industry Alignment65
C · Market Momentum
Category Growth78
Trend Velocity66
Competitive Density45
D · Growth Signals
Funding75
Hiring Growth68
Developer Traction82
E · Execution Readiness
Marketplace Readiness71
Sales Maturity64
Co-Sell Readiness69
Customer Evidence73
F · Risk Signals (higher = worse)
Product Risk30
Platform Risk25
GTM Risk35
Financial Risk28
Score Output
79
Final Score
Tier 1
Strategic Alignment—
Market Momentum—
Growth Signals—
Execution Readiness—
Risk Score—
Confidence Score—
Exploration Score—
Allocation Bucket—
Budget Estimate—
Formula
final_score = (
0.45×ml + 0.20×strategic
+ 0.15×momentum + 0.10×growth
+ 0.10×execution - 0.10×risk )
0.45×ml + 0.20×strategic
+ 0.15×momentum + 0.10×growth
+ 0.10×execution - 0.10×risk )
Budget Controls
Adjust ratios — allocation register updates live
Total Budget
$100M
Exploit Ratio: 70%
Explore Ratio: 20%
$70M
Exploit
70%
$20M
Explore
20%
$10M
Strategic
10% (remainder)
Allocation Register
Per-ISV budget · live recalculates with controls above
| ISV | Score | Conf. | Tier | Bucket | Recommended | % of Bucket | Status |
|---|
Bucket Logic
if tier==T1 and conf>70:
bucket = "exploit"
bucket = "exploit"
elif exploration>70:
bucket = "explore"
bucket = "explore"
else:
bucket = "standard"
bucket = "standard"
// Constraints
max_per_isv = 5% × total
min_explore = $50,000
Budget Utilization
4 ISVs awaiting review · Target <2 min/ISV
0 reviewed this session
AI Labeler · Input
Structured ISV profile for LLM evaluation
Prompt Template
You are evaluating an ISV for Azure Marketplace investment.
Score (0–100): strategic_alignment, market_potential, growth_potential, risk_level
Then assign tier · confidence · investment_recommendation · rationale
Respond ONLY with valid JSON.
Score (0–100): strategic_alignment, market_potential, growth_potential, risk_level
Then assign tier · confidence · investment_recommendation · rationale
Respond ONLY with valid JSON.
AI Evaluation Output
⟡ Run evaluation to see AI scores
Continuous Learning Loop · IntelligenceIQ Framework
TrendIQ
Data ingestion · feature scoring · market signals
DecisionIQ
ML scoring · tiering · allocation
ActionIQ
Budget deployment · manager HITL · labels
EffectivenessIQ
Outcome tracking · recalibration · retraining
Feedback Metrics
Azure Consumption Growth+34% avg
Marketplace Transactions12,847
Pipeline Generated$218M
Avg Time to Publish18 days
Tier 1 Hit Rate84%
Missed High Performers3 identified
Adjustment Signals
Managers consistently override for AI-native ISVs → Increase weight of
ai_usage_scoreModel underestimates early-stage startups → Adjust
growth_signal weighting upwardNext RecalibrationIn 3 days
Labels Accumulated189 / 247
Active Learning Priority Queue
ISVs flagged for human review by priority formula
review_priority = high_score × high_uncertainty + disagreement_score + budget_impact
| ISV | Uncertainty | Disagreement | Budget Impact | Priority | Action |
|---|---|---|---|---|---|
| CyberNova Labs | High (48) | +12 pts | $2.4M | 91 | |
| DataForge AI | High (52) | +8 pts | $1.1M | 87 |
MVP Implementation · 3 Phases
Phase 1
Foundation
Weeks 4–6
Use existing ML score
Manual scoring (Excel / Power BI)
Implement scoring formula
Basic tiering logic
Phase 2
Automation
Weeks 6–12
Automate data ingestion
Build scoring API
Portfolio allocation logic
Manager review UX
Phase 3
Intelligence
Weeks 12+
Exploration optimization (bandits)
Real-time feedback loop
Auto-retraining pipelines
Active learning queue
System Architecture
⬡
Data Layer
ISV features · internal + external signals
↓
◎
Scoring Engine
ML + dynamic signals → Final Score
↓
◈
Portfolio Allocation Engine
Tier · Budget · Investment strategy
↓
↻
Feedback Loop
Continuous improvement · HITL labels
Success Metrics
SHORT-TERM
Manager–Model Agreement↑ Target 85%
Decision Speed<2 min / ISV
MEDIUM-TERM
Tier 1 Hit Rate↑ from 84%
Missed Opportunities↓ Reduce
LONG-TERM
ROI per $ Invested↑ Maximize
New ISV Trend AdaptationAuto