Engineered for mid-to-large RIAs, family offices, and wealth managers managing $10M to $500M+ portfolios. Replace bloated legacy monoliths with high-performance, bespoke trading engines built exactly to your workflows.
Before any software conversation, it helps to be honest about what the current process costs. For most advisory firms, turning an investment decision into executed orders is still a chain of manual steps.
Analyst allocation percentages are copied into spreadsheets and converted into per-account share counts by hand, every rebalance cycle. The sheet becomes the system of record, and one person becomes its only maintainer.
While the trade sheet is being built, prices move. Orders sized on stale numbers leave accounts out of line with the model before a single ticket is sent.
Each manual copy and re-check is a chance for a transposed ticker, a buy entered as a sell, or an account that is silently skipped. These errors are small, expensive and hard to catch after the fact.
Firm-wide restricted lists, account-level limits and live prices are verified visually, line by line. That turns compliance into a bottleneck that scales linearly with the number of accounts.
Traditional platforms are built for the average firm. If your process is distinctive, you end up bending it to fit the software, or maintaining spreadsheets around it.
Traditional monolithic platforms serve a broad market, and that breadth is the constraint. Your process has to bend to their data model, their release schedule and their configuration surface.
Per-seat and asset-based pricing grows with your headcount and AUM, while you use a fraction of the feature set. Custom software is a build cost plus lean infrastructure, not a rent that rises with every hire.
Proprietary signals, custom asset classes and bespoke allocation rules usually end up in spreadsheets bolted onto the platform, which recreates the manual risk you were trying to remove.
When accounts sit across several custodians and brokers, off-the-shelf tools often force you to run the same rebalance several times, or to reconcile the results by hand.
We build tailormade execution infrastructure for firms that run on their own process.
Mid-to-large RIAs that have outgrown spreadsheet-driven rebalancing and need repeatable, auditable order generation across hundreds or thousands of accounts.
Single-family offices with their own allocation logic, private holdings and restriction rules that no packaged product models well.
Teams coordinating many client accounts and custodians who need consistent execution, tax awareness and a clean record of every decision.
Small trading firms that need execution tooling and pre-trade controls shaped around a specific strategy, without enterprise platform overhead.
The architecture is a short, observable pipeline. Each stage has one job and writes to the audit log.
An analyst percentage list or a model portfolio is loaded through a form, file or API. Inputs are validated before anything else runs.
A Python and pandas allocation engine converts percentages into per-account share quantities, across buy, sell, short and cover instructions.
A live WebSocket price feed checks each order against the market. If a price has drifted beyond your threshold, the order is held, not sent.
Firm-wide ticker restrictions and account-level limits are checked automatically. Breaches are blocked and explained before they can reach a broker.
Approved orders are exported in your broker's format or sent over a direct API, with a record of what was generated, checked and sent.
Each engagement is scoped to your workflow. These are the building blocks we most often assemble.
Turn analyst allocation percentages into checked, compliant per-account share orders across buy, sell, short and cover instructions in under 30 seconds.
Live WebSocket price feeds and automated constraint checks make sure orders never breach firm-wide ticker restrictions or account-level limits before they reach your brokers.
Tailored integrations built directly into your existing operational tech stack, so the platform fits the custodians and brokers you already use.
Optimized allocation math that accounts for tax considerations, such as lot selection and wash-sale awareness, and runs reliably at scale.
Custom is not always the right answer, and we will tell you so. Packaged software is usually the better choice when most of the following are true.
When several of the second list apply, a custom build tends to pay back quickly: you remove recurring license cost and manual hours, and you own the logic that differentiates you.
CTOs and COOs should know what they are buying. We build on Python and Flask microservices, with low-latency WebSockets for live market data and secure cloud state management for orders, accounts and audit trails. Services are small, documented and yours to own.
The same discipline keeps infrastructure lean. A well-designed execution engine does not need an enterprise hosting bill: high-volume order generation and checking can run for under $100 a month.
The platform generates and validates orders. Assets stay with your custodians, and the system never takes custody of client funds.
Every input, calculation, check and decision is written to an append-only log, so you can reconstruct exactly why an order was or was not sent.
Data and credentials for different firms, entities or books are separated by design, with scoped access, so one workspace cannot read another.
Every build follows the same four-step engineering discipline: Map, Bound, Instrument, Govern.
01
We map your current workflow end to end: where allocations come from, how orders are built, which checks exist and which systems are involved.
02
We define what the system will and will not do: the rules it enforces, the limits it applies and the human approvals it requires.
03
We build with logging, monitoring and cost visibility from day one, so every order and check is observable and measurable.
04
We hand over with controls, documentation and an operating runbook, including a kill switch, so your team stays in charge of the system.
Typical delivery windows run from 4 to 12 weeks, depending on scope. The factors that move a project within that range are:
Prior work by our team
Automated rebalancing and compliance checks for a U.S. registered investment adviser, replacing a manual trade-sheet process.
Delivered by members of our team before Canvas Labs Partners was founded. About this work
Read the case studyYes. Integrations are built per custodian and broker, using direct APIs where they exist and file-based exports where they do not. Scope depends on which institutions you use and what each one exposes, and we confirm that in the scoping call.
A live WebSocket price feed compares each order against the current market. You set the tolerance, and if a price has moved beyond it between sizing and sending, the order is held for review instead of being sent at a stale price.
You do. The code, deployment configuration and documentation are handed over, and the system runs in your own cloud account. We design it so a competent Python team can maintain it without us.
That is your choice. Many teams take the handover and run it in house. Others keep us on a lightweight retainer for monitoring, broker API changes and new rules. Either way, the runbook and logging are built in from the start.
No. The execution logic is non-custodial: assets stay with your custodians. Orders are generated and validated by the system, and you decide whether they go out through a human approval step, a broker export or a direct API.
Most engagements land between 4 and 12 weeks. Scope depends on the number of custodians, the complexity of your allocation and tax logic, and your compliance rules. We give a fixed scope and estimate after a technical scoping call.
Talk directly to the financial infrastructure engineers who will write the code. Bring your allocation process, your custodians and your compliance rules, and leave with a scoped plan.