Analysis Provenance
| Project Name |
LocalPerks - Local Loyalty Coalition |
| Generated At |
2026-01-05 15:05:50 UTC |
| AI Model |
z-ai/glm-4.7 |
| Execution Mode |
Sequential |
| Total Time |
25m 58s |
| Tool Version |
VenturePulse v2.0 |
Cost Breakdown
| Section |
Tokens |
Cost (USD) |
| 01. Executive Summary |
14,546 |
$0.023 |
| 02. Market Landscape |
24,158 |
$0.039 |
| 03. User Stories |
14,398 |
$0.021 |
| 04. Comparable Companies |
16,096 |
$0.023 |
| 05. User Research |
16,765 |
$0.025 |
| 06. Validation Experiments |
16,228 |
$0.026 |
| 07. Technical Feasibility |
18,482 |
$0.030 |
| 08. Competitive Advantage |
20,609 |
$0.034 |
| 09. Business Model |
21,260 |
$0.033 |
| 10. Legal & Compliance |
0 |
$0.00 |
| 11. MVP Roadmap |
0 |
$0.00 |
| 12. Customer Journey |
0 |
$0.00 |
| 13. Go-to-Market |
0 |
$0.00 |
| 14. Partnerships |
0 |
$0.00 |
| 15. Expansion Plan |
0 |
$0.00 |
| 16. Success Metrics |
0 |
$0.00 |
| 17. Funding Strategy |
0 |
$0.00 |
| 18. Exit Strategy |
0 |
$0.00 |
| 19. Pitch Narrative |
0 |
$0.00 |
| TOTAL |
162,542 |
$0.255 |
Failed Sections (10)
| Section |
Error |
| 10. Legal & Compliance |
Unexpected error: 'int' object has no attribute 'lower' |
| 11. MVP Roadmap |
Unexpected error: 'int' object has no attribute 'lower' |
| 12. Customer Journey |
Unexpected error: 'int' object has no attribute 'lower' |
| 13. Go-to-Market |
Unexpected error: 'int' object has no attribute 'lower' |
| 14. Partnerships |
Unexpected error: 'int' object has no attribute 'lower' |
| 15. Expansion Plan |
Unexpected error: 'int' object has no attribute 'lower' |
| 16. Success Metrics |
Unexpected error: 'int' object has no attribute 'lower' |
| 17. Funding Strategy |
Unexpected error: 'int' object has no attribute 'lower' |
| 18. Exit Strategy |
Unexpected error: 'int' object has no attribute 'lower' |
| 19. Pitch Narrative |
Unexpected error: 'int' object has no attribute 'lower' |
Disclaimer: This analysis was generated by AI and should be used as a starting point for decision-making, not as definitive business advice. Always validate assumptions with real market research and domain experts.