AI Agents for Wealth Management

In wealth management, an agent is defined by the judgment around it as much as its capability: the data it reads, the advice boundary it holds, the point where it defers to an adviser. It earns a place in client work only when its structure can be trusted as much as an adviser's own.

Tecla builds and operates these systems inside your environment, held to the same standards your advisers answer to.

The shift underway

AI has reached most advisory firms; making it part of how the firm runs day to day is the harder, unfinished half. The numbers show how far adoption has gone, and how much room is left.

63%

of RIAs now use AI, double the 2023 rate.

Source: Charles Schwab

1 in 10

has fully integrated AI. The rest is experimentation.

Source: Charles Schwab

40–60%

of RIAs run modern portfolio systems.

Source: Envestnet

Find out where an agent would give your advisers time back

A scoping conversation identifies the workflow worth automating first, and what it would take to build it. Free of charge.

Scope a Build

The state of AI in wealth management

Advisers have adopted AI. Almost none of it has reached the client.

Adoption is nearly universal. Around 63% of independent RIAs now use AI in some form, more than double the share in 2023, and most advisers already lean on it for notes, drafts, and research.

The revealing number is a smaller one. Only about one firm in ten has integrated AI into how the practice actually runs. Adoption is close to universal; integration is close to zero.

The cost of that gap is time. Advisers still spend close to 70% of the day on preparation, reconciliation, and compliance, and only a third with clients. What closes it is less the model than the structure around it: what the agent reads, what an adviser reviews, where it hands back.

Tecla has spent more than a decade placing senior engineers inside US companies. It builds agents the same way it places people, scoped and supervised, and operates them so they hold up against real client work long after the demo.

The structure around the model

How a system gets built, run, and owned

The reliability an agent needs comes from the arrangement around it: a scoped brief, a named team, and someone accountable at every stage. This is what that looks like from first call to a system you own.

Sprint

Scope, fixed price

We map the workflow, the data access, the decision limits, and the metrics that will tell you it works, then return a plan and a price before you commit.

AI Solutions Lead

Build

Built into your environment

Senior engineers build the agent in your environment and integrate it with the data and systems you already run.

AI Systems Lead

Run

Monitored and improved

Through Managed Operation we keep the system reliable, report against the metrics set at scope, and improve it as data and workflows change.

Systems Lead + Engineers

Own

Yours, improving

You own the system end to end, and it sharpens over time instead of aging into a tool nobody maintains.

Your team

Where we put it to work

One agent per workflow, specialists inside

The same approach applies across the practice. Each system takes on one workflow an adviser or their team runs by hand today, from portfolio monitoring to client prep, inside the tools you already use.

Client Lifecycle

From first proposal to funded account, the work that turns a prospect into a client.

Client Onboarding Agent

Runs onboarding from signed agreement to funded: collects data once, fills custodial forms, and catches NIGO before submission.

client onboarding automation · NIGO

Proposal & IPS Agent

Scans a prospect statement, compares portfolios, and drafts a branded proposal and IPS in minutes.

investment proposal · ips automation

Meeting Prep Agent

Assembles the briefing before every client meeting from the CRM, portfolio, and plan.

ai meeting prep for advisors

Portfolio & Planning

Managing the money and building the plans, from monitoring and rebalancing to retirement and estate.

Portfolio Monitoring Agent

Watches every account for drift, risk, and opportunity, and prepares the work an adviser reviews.

ai portfolio monitoring

Portfolio Rebalancing Agent

Builds tax-aware rebalancing trades across the household and routes them on approval.

ai portfolio rebalancing

Tax-Loss Harvesting Agent

Scans taxable accounts daily for harvestable losses, respects wash-sale rules, and prepares the trades.

tax-loss harvesting automation

Direct Indexing Agent

Builds and maintains custom index sleeves, applies screens, and harvests at the position level.

direct indexing automation

Held-Away Account Management Agent

Manages outside 401(k)s and held-away accounts through compliant, permissioned access.

held-away account management

Account Aggregation Agent

Pulls each client's full financial picture into one place and keeps the data clean as feeds break.

account aggregation for advisors

Financial Planning Agent

Turns client data into a first-draft plan with projections and scenarios for the adviser to own.

ai financial planning

Retirement Planning Agent

Builds the income plan behind retirement: drawdown sequencing, Monte Carlo, and claiming decisions.

ai retirement planning

Estate Planning Agent

Reads wills, trusts, and beneficiary documents, and surfaces the planning gaps an adviser should raise.

ai estate planning

Reporting & Operations

The recurring back-office work: client and performance reporting, billing, and cross-tool workflows.

Client Reporting Agent

Assembles client reports and drafts commentary from verified figures, ready for the adviser to send.

client reporting automation

Performance Reporting Agent

Consolidates multi-custodian data, calculates returns and attribution, and reconciles every figure.

performance reporting software

Fee Billing Agent

Runs the advisory fee cycle: calculates against each schedule, reconciles, and flags exceptions.

ria fee billing software

Advisor Workflow Agent

Runs the repetitive cross-tool work between the CRM, portfolio, custodian, and document systems.

advisor workflow automation

Compliance

Keeping the firm exam-ready as AI multiplies the communications a compliance team must review.

Compliance Review Agent

Reviews marketing, communications, and advice against your policies and flags what needs an officer.

ai compliance review for advisors

Start the build

Begin with the workflow that matters most

A scoping call maps your highest-value advisory workflow and returns what an agent would cover, how success gets measured, and what the fixed-price Sprint to build it costs. One system, measured in production, before you expand.

Scope your first wealth agent

Read the use-case guide

Fixed-price AI Systems Sprint. No commitment until scope is confirmed.

What wealth leaders ask about AI agents

What is agentic AI in wealth management?

Agentic AI describes systems that work through a task the way a person would: reading context, pulling data, deciding, and acting. In wealth management, an agent can prepare a client review, monitor a portfolio, or research a prospect end to end. Tecla builds these into your own stack, not as a fixed product.

How is an AI agent different from the automation we already run?

Rules and RPA follow fixed steps and break when the input changes. An agent weighs context, handles exceptions, and explains its reasoning, covering the judgment work scripts cannot. Tecla builds on top of your existing automation, taking over the steps where analyst time goes.

Which advisory workflows are the best fit for AI agents?

The strongest fits are data-intensive workflows an adviser repeats for every client: portfolio monitoring, meeting preparation, proposal drafting, prospect research, and onboarding. Tecla starts with one, ships it, then expands, rather than attempting everything at once.

Do we own the agents Tecla builds, or license them?

You own them. Tecla builds each system in your environment, on your data, with no platform lock-in. The system runs under your control and access rules, which is usually the first thing a regulated institution asks about.

How does Tecla handle security and compliance for advisory firms?

Agents run inside your environment, with human-in-the-loop controls, tool-call limits, and audit trails from day one. A person makes the final call on any risky decision, and every action is logged. Compliance requirements are scoped per engagement, not promised in the abstract.

Why do so many AI agent pilots fail to reach production?

A demo is quick to build. A system an advisory firm trusts needs real data integration, evaluations, and lasting oversight, which is where efforts stall. Tecla's model targets that gap: a Sprint to scope it, a named pod to build it, and Managed Operation to keep it current.

How long does it take to get an agent into production?

Tecla starts with a fixed-price AI Systems Sprint that scopes and prices the build before you commit. Because each engagement begins with a focused build, the agent reaches your stack in weeks rather than a multi-quarter program, then continues to improve once live.

We have an internal data or engineering team. Where does Tecla fit?

Alongside them. Many institutions have the talent but not the spare capacity to take an agent from prototype to a maintained production system. Tecla builds it with your team, hands over a system you own, and stays on for ongoing operation only where that keeps creating value.

Who works on a Tecla engagement?

A small forward-deployed pod: a US AI Solutions Lead on the commercial side, a senior LatAm AI Systems Lead who owns the technical build and stays your point of contact, and AI Systems Engineers who build and maintain it. US commercial leadership, nearshore technical delivery.

How do we get started with Tecla?

Book a scoping call. Tecla reviews your highest-value advisory workflow, the data, and the systems already in place, then returns what an agent would cover, where it plugs in, and what the AI Systems Sprint to build it would cost. No commitment until scope is confirmed.

Have any questions?

Schedule a call to discuss in more detail.

Book a Call

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