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Moving Size Shouldn't Feel Like Guesswork
When every basis point matters, block execution is still stuck in spreadsheets, email chains, and outdated TCA. You’re relying on trader intuition, partial market color, and post-trade analytics when the real impact lies in pre-trade intelligence and execution automation.
Where Block Execution Breaks Down
Traders lack visibility into hidden liquidity and dark pool conditions before placing blocks
Execution quality depends heavily on individual experience, not standardized workflows
Market impact is reactive — slippage only measured after the fact
Routing decisions across venues are manual and time-sensitive
Buy-side desks operate with fragmented tools and limited data consolidation
Our Solution
We’ve built a modular block trading intelligence layer that surfaces actionable liquidity signals, automates workflow decisions, and improves execution across fragmented venues.
Solution Components:
Liquidity Signal Engine – Aggregates historical fills, dark pool activity, broker quotes, and public depth
Pre-Trade Sizing Module – Recommends optimal order sizing to reduce impact and improve fill probability
Routing Intelligence Agent – Suggests optimal venue, timing, and broker routing paths based on past outcomes
Execution Analytics Layer – Real-time feedback on slippage, child order pacing, and algo performance
Output Delivery – Data integrated directly into your OMS, TCA platform, or execution layer via API, flat file, or live feed
Common Use Cases
Traders receive real-time recommendations on block size thresholds and routing based on historical fill performance
Liquidity maps flag risk of adverse selection across venues before routing
Desk leads monitor block execution quality and market impact in real time
Teams reduce reliance on manual market color and increase systematic execution quality
Business Outcomes
Reduce slippage by 30–70 bps across large trades
Improve fill rates in hard-to-trade names and low-liquidity windows
Enable real-time routing optimization without additional headcount
Create a feedback loop between execution and strategy teams using structured data