Trading plans evaluated against the firm's actual mandate before capital moves. A behavioral engine that grades its own predictions against fills. A sealed evidence chain on every decision. Deployed single tenant inside the firm's own environment, with no data egress of any kind.
Pre trade compliance evaluates coded limits at the moment an order exists. Surveillance examines executions and communications after the fact. Retrospective analytics reconstruct decision quality from holdings data, months later. Each is necessary. Each is silent about the same thing: the plan, the reasoning, and the sizing logic that formed before any order reached the OMS. Three exhibits from the research behind this product.
Dollar figures are the 94 bps applied to book size, indicative only; the precise number differs by desk. The structural point does not: these biases operate at the intent stage, precisely the stage the current control stack cannot see. Every control the firm runs today fires after this cost is already incurred.
SOURCE · Essentia Analytics client research, stated publicly by CEO Clare Flynn Levy (Markets Media interview and company publications, 2020). Essentia's decision analysis methodology is published in the peer reviewed Journal of Investing.
The direction is singular: regulators increasingly expect a record of how decisions are made, not only of what was executed, and governance of any AI that touches those decisions. An intent stage record, generated and retained inside the firm's own walls, is built for exactly this trajectory.
SOURCES · U.S. SEC, Electronic Recordkeeping Requirements adopting release, October 12, 2022 · Advisers Act Rule 204-2(a)(7) · SEC recordkeeping enforcement orders, September 2022 onward · Regulation (EU) 2024/1689 and the European Commission's published implementation timeline.
AI governance now appears on most institutional operational due diligence checklists, and is identified among the fastest growing areas of allocator scrutiny.
SOURCES · EY operational due diligence priorities analysis, 2025, as reported in industry ODD guidance · AIMA Illustrative Questionnaire for the Due Diligence of Investment Managers.
DojiPad Institutional replaces nothing and competes with nothing. Every incumbent control fires somewhere on the decision timeline. We took the one position on it that was empty, and it happens to be the position where the decision is actually made.
Read the timeline left to righttop to bottom and the pattern is plain: the further rightfurther down a control sits, the more it can prove and the less it can change. By order entry the thinking is done. By execution the money has moved. By review the quarter is over. The intent stage is the only point where evidence and influence coexist, and until now nothing has operated there.
One firm operates closest to this space, and deserves to be named rather than gestured at.
Essentia established the category: behavioral analytics for professional investors, and the published evidence that decision level behavior carries a measurable cost. We consider that work foundational. Characterizations of Essentia are based on publicly available product descriptions as of mid 2026. Retail journals and coaching apps are not compared here; none operate inside a firm tenant, carry a mandate register, or produce supervisory records.
The difference is architectural, not incremental. Essentia analyzes decisions after they are made, from data that leaves the firm. DojiPad Institutional supervises decisions while they are being made, from inside the firm's own walls. One is a mirror held up quarterly. The other is an instrument in the cockpit. A desk can reasonably run both; only one of them exists at the moment the plan can still change.
One diagram carries the whole design. Market data and fills flow in. The dialogue circulates between trader and coach and never leaves that plane. Committed plans cross one boundary, to the officer register. Orders travel the firm's own execution path, which runs around this system entirely. And nothing, of any kind, leaves the tenant.
The entire system deploys inside the firm's own cloud subscription, under the firm's identity provider and the firm's keys. There are no external calls, no telemetry, and no vendor infrastructure the firm's data could reach. The vendor cannot see the firm's trades. That is a property of the architecture, not a contractual promise.
The firm plane carries mandate evaluations, observations, and evidence chains, and is built for risk and compliance officers. The trader plane carries the coaching dialogue itself and is structurally separated: never summarized, scored, or flagged across. Coaching runs on candor, and candor requires a boundary that cannot be reconfigured away.
Each trader's specific failure patterns are modeled from their own history. The engine issues falsifiable predictions before a session and grades itself against actual fills. Every claim the system makes about a trader is scored against execution data, and the scoreboard is part of the product.
A discretionary desk has exactly one asset: the judgment of its traders. Every control the firm buys should be measured against one question. Does it make that judgment better, or does it merely constrain it?
A wall produces compliance at the moment of the wall and nothing afterward. An observation, surfaced while the decision is still open, with the trader's own record and the mandate's own words attached, produces something a wall never can: a trader who catches the pattern themselves next time. One of these compounds across a career. The other has to fire again tomorrow. We chose the control that compounds, and the system's design follows from that choice completely.
Aviation did not become the safest form of travel by automating pilots out of the cockpit. It did it with instrumentation, checklists, and a culture where every decision leaves a record and every record teaches. That is the model here. The trader decides. The firm supervises. The system makes both happen with full information at the intent stage, and seals the evidence that they did. Judgment stays where the returns come from, and so does the accountability.
We do not ask desks to take a young vendor on faith, and we do not hand out our technology to prove ourselves. What we show instead is where the rules are going and what the system already implements for each. The full mapping is available as a memo, and the architecture is reviewed live with the firm's security function under NDA.
Bloomberg and Charles River do not publish their internals, and neither do we. What a serious vendor owes a serious counterparty is not source code. It is evidence of understanding the obligations the counterparty actually carries, and a system already shaped to them.
DojiPad Institutional is built by ARQNXS, the firm behind DojiPad, a behavioral coaching platform for discretionary traders. Founder Nigel van der Laan is a discretionary order flow trader with a background in biopsychology and neuroscience, building trading infrastructure since 2017.
The behavioral engine was proven on the retail platform: model a trader's specific failure patterns, evaluate plans before execution, grade every prediction against fills. The institutional system wraps that engine in the deployment architecture professional desks require, and in the design decisions their traders will accept.
Four short papers on the thinking behind the system, publishing weekly. Subscribers receive each one on release.
The system running live, on a seeded demonstration firm, viewed from the officer register and the trader plane in turn. Attendance from the risk function is welcome and usual.
A briefing is the system running live, on a seeded demonstration firm, viewed from both planes. A regulatory alignment memo is available in advance on request.