AI-powered chain selector for max TPS routing in Web3 apps
Enterprise teams are frustrated by scalability issues in Web3 blockchains that deliver insufficient TPS for real-world business applications.
ChainSurge analyzes live TPS and routes transactions to the optimal L1/L2 for your use case. It learns from your app's patterns to predict and balance loads. Enterprise teams integrate via API/SDK for seamless high-TPS failover.
Enterprise teams developing or deploying Web3 blockchain solutions requiring high TPS for production business use cases.
ML model trained on your tx history for personalized chain routing
supportive
Route tx to best chain
Forecast chain performance
Distribute tx across chains
Visualize decisions and savings
Define routing logic
Auto-switch on failures
Improve with app data
X-chain asset moves
Combine with batching
Scenario testing
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| name | text | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| app_id | uuid | No |
| from_chain | text | No |
| to_chain | text | No |
| timestamp | timestamp | No |
| tps_used | int | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| app_id | uuid | No |
| weights | text | Yes |
Relationships:
/api/routeGet optimal chain for tx
/api/apps/:id/routesHistory of routings
/api/rulesUpdate routing rules
/api/predict/:chainTPS prediction
3 chains
10 chains
None
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 120 | 2% | $58 | $696 |
| Month 6 | 600 | 4% | $696 | $8,352 |
AI picks the highest TPS chain for every tx – scale effortlessly.
Target L2 projects on Twitter/LinkedIn, provide free audits of their chain usage via DMs, convert top 3 with custom integrations.
DEX agg
Swap-only
General tx routing
RPC relay
No AI selection
Intelligent TPS focus
Proprietary ML models per app creating switching costs
Multi-chain world maturing, enterprises need unified high-TPS access
ML accuracy
Fallback rules + monitoring
Integration friction
SDK + templates
High compute costs
Edge ML
Success: 5 interests
Success: 20% TPS uplift
Success: 10% MoM growth
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