Market Structure: Reduce Extreme Slippage With Batch Execution
JIL improved execution predictability using batch clearing and oracle bands with audit-grade batch receipts.
Scenario at a glance.
Liquidity + Routing Partner (Scenario)
Global
Market Structure / Liquidity
AMM V5 Batch Auctions + Oracle Bands + Receipts
Benchmark-based analysis.
Public-benchmark inputs paired with the JIL control surface that addresses each one. Modeled impacts are derived from public benchmarks and the control changes enabled by JIL Sovereign.
The institutional requirement is defensible execution narratives with audit-grade evidence.
Timed batch auctions + oracle bands + deterministic batch receipts.
Batch mechanics can reduce extreme slippage events by 10-35% on large-notional swaps (modeled; depends on liquidity/routes).
Estimated value improved = large-swap notional x slippage proxy x (10-35%).
Batch receipt ID + execution timeline + exportable pack.
Institutions buy execution integrity and a defensible clearing narrative. JIL Sovereign Technologies, Inc.
What changed, and what was measured.
Large swaps suffered from MEV/sandwich behavior and unpredictable execution.
- Reduced extreme slippage events (target KPI)
- Improved predictability with deterministic batch IDs
- Produced audit-friendly execution receipts
Why this problem persists
In standard AMM pools, large swaps are visible in the mempool before execution. MEV bots sandwich these trades - buying before and selling after - extracting value from the trader. The result: unpredictable execution and extreme slippage. In this scenario, the liquidity partner was routing institutional-sized orders through standard AMM pools and consistently experiencing adverse execution. MEV extraction was measurable and growing, and clients were losing confidence in execution quality.
The JIL approach
JIL's AMM v5 uses commit-reveal batch auctions with VRF-randomized ordering. Trades are committed (hidden), then revealed and executed in randomized batches. Oracle bands reject trades that deviate beyond expected price ranges. Every batch produces a deterministic receipt. The commit-reveal scheme prevents front-running by hiding trade details until the batch window closes. VRF-randomized ordering within each batch eliminates ordering manipulation. Oracle bands provide a price sanity check that rejects trades with extreme deviation, protecting against manipulation during volatile periods.
Scenario parameters
| Corridor | AMM trading with large institutional orders |
|---|---|
| Monthly Volume | Pilot cohort |
| Risk Class | Medium |
| Integrations | AMM v5 + oracle feeds + batch clearing engine |
| Evidence Outputs | Batch receipt + execution log + oracle band verification |
Every settlement event produces verifiable evidence.
Settlement Receipt
Intent Attestations
Policy Log
Audit Export
The control surface, compared.
- Visible mempool orders
- MEV/sandwich attacks
- Unpredictable execution
- No execution audit trail
- Hidden commit-reveal
- VRF-randomized batches
- Oracle band protection
- Deterministic batch receipts
The control mechanics that moved the metric.
hides trade intent until batch execution
eliminates front-running opportunity
reject trades with extreme price deviation
audit-grade execution evidence for every batch
Deployment path
Expand oracle band integration to additional price feeds, deploy institutional RFQ venue alongside AMM, and integrate batch receipts with institutional reporting systems.
Begin a principal-level conversation.
These scenarios demonstrate deployed JIL capabilities against documented industry problems. The reference mainnet runs 301 production services across 10 active SCN validators today, scaling to 20 active with 20+ standby across 13+ jurisdictions, executing the full 175-check production catalogue with under-two-second pre-settlement verdicts.