Trade Rebalancing & Compliance for Investment Advisers
Capital Markets / RIATurning analyst allocation percentages into checked, compliant per-account trade orders in under 30 seconds, for an adviser rebalancing $10M to $100M portfolios.
Overview
A U.S. registered investment adviser rebalancing portfolios worth $10M to $100M for each client needed trade orders prepared and checked in minutes, not hours. Canvas Labs Partners built an automated trade execution and compliance engine that turns allocation percentages into checked, compliant per-account orders, validated against live prices and firm trading restrictions.
Trade prep in under 30 seconds
down from roughly two hours per cycle
$100M+ rebalanced daily
across client accounts, fully automated
Runs for under $100 a month
total infrastructure cost for the engine
Challenge
The desk prepared every trade by hand in spreadsheets, translating analyst allocation percentages into exact per-account share orders across buy, sell, short and cover instructions. Every line then had to be re-checked against live prices before it could be sent to the broker, repeated for each account in the rebalance before any order went out.
Solution
Canvas Labs Partners built a REST service, written in Python with Flask, that converts each analyst's percentage allocations into exact per-account share quantities across all four order types the desk uses: buy, sell, short and cover. What used to be a manual calculation comes out the other side as a ready order line.
A live WebSocket price feed checks every order line the moment it is generated, automatically rejecting any sheet whose price has drifted more than 7 percent from the current market. Firestore holds the running state behind the service, and pandas handles the allocation math across every account in the rebalance.
A constraint engine runs last, checking every order against firm-wide ticker restrictions and each account's own trading limits before anything is exported. An order that fails a price check or a restriction never reaches the export file, so the sheet that reaches the broker has already cleared every check the firm requires, without anyone checking each line by hand.
Results & benefits
Trade-sheet prep now takes under 30 seconds per cycle, down from roughly two hours of manual work translating allocations into share orders and re-checking them by hand. The engine rebalances more than $100 million in trade value a day across client accounts, with every order already validated against live prices and firm trading restrictions before it reaches the broker. It runs on infrastructure costing under $100 a month, and the checks that used to depend on someone catching a mistake by reading every line now happen automatically on every order, every cycle.
Customer
U.S. registered investment adviser
Services
- Trading & quantitative infrastructure engineering
- Compliance & constraint engineering
- Real-time market data integration
Tech stack
About us
Canvas Labs Partners is a software consulting team that designs and ships production agentic AI systems: multi-agent pipelines, tool-calling architectures, and human-governed automation, together with the trading infrastructure, blockchain, mobile, and product engineering those agents plug into. We publish our work as a case ledger rather than a portfolio, so every claim on this site links to the engagement behind it. Engagements follow the same four-step discipline, Map, Bound, Instrument and Govern, whatever the stack, and every entry in the ledger carries a result we are willing to be measured against.
Delivered individually, in a prior role, by one of Canvas Labs Partners’ founding team members. Not by the firm itself.
Have a system like this one?
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