Your advisors are already using AI. The only question is whether your firm can prove it's governed. What RIAGuardrAIls supplies is the guardrails: a governed tool layer between the model and your book — every seat scoped, every figure computed by a tool rather than guessed by the model, every request memorialized on a record you own.
Built and operated by a sitting Chief Compliance Officer of an SEC-registered investment adviser — running in production, on the record, every day.
The people building AI tools and the people who answer to examiners for them are usually different people. Here, they're the same person. That changes what gets built — and what would never be allowed to ship.
Generic AI tools don't know your book — so advisors paste client names, accounts, and holdings into chat windows by hand. That workaround is the violation: unlogged, unscoped, unretained.
Regulators fined firms over $2 billion for business communications on unapproved channels employees used anyway. Ungoverned AI is the same pattern on the next channel — and examiners are already asking about AI use.
Amended Reg S-P requires safeguarding customer information and notifying clients of compromise. PII pasted into a consumer AI tool sits outside your safeguards, your vendor diligence, and your incident response.
Advisers must preserve required business records under Rule 204-2. AI conversations that shape advice, held in personal accounts, are records you cannot produce.
This posture has already been charged: in the off-channel sweep, an adviser whose own senior officers violated its written prohibition — never verified — was charged for the policy failure itself. $6.5 million, required admissions, an imposed consultant.
SEC off-channel communications sweep, 2021–2024 · In re Senvest Management LLC (2024) · Reg S-P amendments (2024) · Advisers Act Rule 204-2 · SEC 2025 Examination Priorities (AI use). Examination dialogue is an illustrative scenario.
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Fourteen sections — including AI accuracy and hallucination — the tool-inventory template, and the evidence checklist your examiner will read it against.
Data connects server-side — client identifiers stay in your database, and advisors get answers without ever pasting raw account or client information into a prompt. The AI works against your book without handling the PII itself.
Each AI data request writes an audit entry — who asked, what was accessed, when, and the outcome. When the examiner asks for your AI records, you produce a log, not a shrug.
Each advisor's AI sees only that advisor's book. No entitlement means access to nothing — never everything. Executives and compliance get the firm-wide view by role, on the record.
Each firm runs a dedicated deployment — its own database, its own encryption keys, its own domain. Client data never commingles with another firm's, never gets copied into a vendor's cloud to build someone else's "canonical record," and the instance is yours.
Generative models produce fluent, plausible, wrong figures — the single risk every compliance officer names first. Here, the model never computes a number: every figure on screen is calculated by a governed tool reading your systems of record, and carries its provenance. An invented balance, return, or RMD structurally cannot appear — accuracy by architecture, not by hoping someone catches it in review.
The canvas opens blank. Ask for your morning, and watch the AI assemble it — book summary, risk overview, review queue — each panel placed and sized by what matters most today, each one receipted as it lands.
Say a household's name, and the entire canvas becomes them. Release, and the firm view returns exactly as you left it. Not a dashboard with a chat bolted on — a governed surface that arranges itself around the work.
Illustrative composition of the governed canvas, sample data.
AI has reset the bar on client deliverables — firms are shipping polished, personal, media-rich work, and clients notice who isn't. Every example below is one ask, answered from your firm's own CRM, custodial, and document data — scoped to the asker, verified against the systems of record, and logged.
Accounts gone inactive, cash past your threshold, meaningful value swings, households untouched in ninety days — a triage list before your first coffee, scoped to your book alone.
Year-over-year trend, current allocation and cash, last review's commitments from the CRM, progress against the plan document. An afternoon of prep becomes one question.
Idle cash, concentrated positions, households that outgrew their service tier, follow-ups promised in the CRM and never made. An entire startup category sells this as a subscription; here it's one ask.
Built from custodial and CRM data, scoped to the advisor, reviewed before it ships. Meeting prep becomes a listen on the drive in.
Alternatives don't show up in custodial feeds — their story lives in statements your reporting stack can't see. Bring those figures in, confirm them, and the report assembles a polished performance picture alongside the rest of the book. The holdings your system can't reach become your best deliverable.
Exam prep flips from dread to a query. The audit trail your policy promises becomes a standing record you produce on demand — the exact evidence the swept firms couldn't.
Three disciplines, enforced in code on every request — not policed after the fact.
Advisors see their clients — never each other's. Principals see the firm, with attribution. Isolation is enforced on every payload element before the first question is answered.
seat: advisor · scope: book:readThe AI works through governed tools — book intelligence, supervision screens, risk analytics, review documents. Writes are dark by default, and confirm-gated when a firm turns them on.
writes: confirm-gated · dark by defaultEvery tool call lands in an audit trail your firm owns — who asked, what ran, whether it succeeded, when. A session can be reconstructed for examination. That isn't a feature; it's the shape of the system.
audit: per-call · session: serializedSo here is exactly how that information is protected, where it goes, where it does not, and how anyone would know if something went wrong. Every line describes a shipped control — what it claims, it can show.
An advisor's connection sees only that advisor's own households and clients; firm-wide visibility requires a firm-level role. The boundary is enforced on every single request — not just at login — and a request that isn't permitted returns nothing at all, without even revealing the thing exists.
fail-closed · enforced per requestClient data lives in a dedicated database only the service can reach, through one locked-down key, with row-level rules that keep every query inside firm and advisor boundaries. Stored credentials are held encrypted, and every connection is encrypted in transit — nothing is served in the clear.
dedicated DB · row-level rules · TLSAvailability is monitored continuously from outside the firm's own infrastructure, so an outage — even one that takes the whole machine down — raises an alert within minutes. Repeated failed sign-ins on every login surface are detected and alert the firm's compliance and executive roles.
external monitor · intrusion alertingEvery privileged action and every write back to the CRM is tied to a named operator and logged — with no client data kept in that trail. Compliance can review the live evidence — failed-sign-in counts, alerting status, system health — in the admin console.
named operator · reviewable evidenceHonest about the limits: this is proportionate, verifiable protection for a governed advisory tool. It is not a 24/7 security-operations center, and this page will never imply it is.
This is operational compliance, not process compliance — evidence computed from real custodial and CRM data, never self-reported. Every capability ships twice: an advisor version scoped to their own book, and a principal version scoped to the firm with attribution. Same math, different blast radius.
Census, holdings, transactions, balance history, and true performance — market return separated from flows.
CRM-vs-custodian conflicts, unbridged assets, householding drift, contribution stoppages, fee outliers.
Firm value-weighted risk, per-advisor ranking, concentration-times-risk screens, single-ticker blast radius.
Strategy mix, covered versus naked exposure, expiry calendars with assignment risk, market-vs-model divergence on live chains.
Deterministic tax and retirement modeling — Social Security claiming, IRMAA tiers including Part D, the senior deduction. Every figure computed by the tool, never by the model, with primary-source provenance.
Meeting prep, annual-review briefs, and wealth progress reports an advisor is proud to hand across the table.
Firm AI activity summarized from the audit trail itself — the layer that watches the layer.
Some platforms make advisors change firms to reach their AI. Here, adoption is a connector consent — your CRM, your custodian, your compliance archive, your comp structure, and your clients stay exactly where they are. What you pay for is the one thing you don't have and shouldn't build twice: the guardrails. The walls, the scoping, the record — that's the product.
Your communications archive. Your marketing-review workflow. Your personal-trading system. RIAGuardrAIls is the governed layer between your firm's AI and your firm's data — access, isolation, and the record. One governed platform can replace the pile of single-purpose AI subscriptions — and under amended Reg S-P, every vendor you retire exits your oversight, diligence, and incident-response perimeter. But we'd rather tell you where the edges are than let you find them.
A well-funded vendor category now sells AI readiness — unifying your data so AI can use it someday, by copying your book into their cloud to build a "canonical record." Readiness is a roadmap; it ships no advisor-facing AI, no supervision surface, and no record of how AI touched client data. RIAGuardrAIls is the AI layer itself: governed tools in daily advisor use, a live supervision surface, and the one artifact no data layer produces — a supervisable record of every AI interaction. If your systems already talk to each other, you don't need a second foundation bought under the first.
The demonstration starts from a blank screen. You watch the governed canvas assemble the morning — every panel receipted as it lands, one contradiction surfaced where you can't miss it. Before the examiner writes your AI policy for you — let's talk.
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