Investment and market research synthesis
Reads filings, research, and market data and drafts a sourced summary for an analyst or advisor to review. Turns hours of reading into minutes, with the human owning the interpretation and the call.
Prepared 86%
- Accounts
- 24
- Drafted
- 18
- Exceptions
- 3
- Portfolio data reconciled Custodian and CRM records Prepared
- Review narrative drafted Performance and talking points Prepared
- Advisor sign-off Recommendation and client release Review
AI for finance and advisory firms, on the research, reporting, and compliance work that eats billable hours
The AI that makes finance headlines is autonomous: agents trading, models deciding. Your firm's drag is quieter. It is investment research, client reporting, meeting prep, and a compliance queue that never clears. Phos AI Labs puts AI on that work, so it drafts, synthesizes, and reconciles. Every investment recommendation, fiduciary judgment, and regulatory sign-off stays with a licensed professional.
AI for finance and advisory firms is the use of AI on research, documentation, reporting, reconciliation, compliance drafting, and client communication, with every investment recommendation, fiduciary decision, and regulatory sign-off left to a licensed professional. Phos AI Labs finds the highest-volume analytical and administrative work draining advisors, analysts, and operations staff, builds the systems that absorb it, and embeds them inside a compliant environment. The judgment calls stay with your people. The paperwork stops eating billable time.
Claude (Anthropic) Partner and Select OpenAI Partner.
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40+ AI systems
shipped to production in the last 6 months.
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Human-owned decisions
AI on the research and documentation layer, with a licensed professional on every recommendation and sign-off.
Trusted across 400+ builds by the LowCode Agency team — Sotheby's · American Express · Coca-Cola · Medtronic · Zapier
Why do most finance AI projects never leave the pilot?
Finance is not short on AI ambition. In wealth and asset management, 95% of firms have scaled generative AI to multiple use cases, per EY. Yet only a little more than one in four executives report substantial business impact. The technology is rarely the reason. The work around it is.
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Adoption is near-universal, and impact is not.
Almost everyone has deployed AI; few have turned it into measurable value. The gap is end-to-end operational change, not another pilot. The firms that close it treat AI as a workflow decision, not a tool purchase.
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Regulation and compliance are harder than expected.
86% of wealth and asset management firms were surprised by the regulatory complexity of scaling AI, per EY. SEC and FINRA obligations, recordkeeping, and disclosure rules are non-negotiable, and when governance is added after the build, the project stops at compliance review.
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The data is fragmented and the models can be wrong.
Client data, portfolio data, and market data live in separate systems, and hallucinations and bias are real risks flagged by three in four firms. AI is only as good as the data it is grounded in and the human who checks the output.
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No one drew the line.
The firms that ship decided, up front, exactly what AI touches and what stays with a licensed professional. Without that boundary, every use case becomes a fiduciary-risk debate, and the safe, high-value research and reporting wins never get built.
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The talent bench is thin.
The future finance workforce needs both domain and AI expertise, and most firms do not have that mix in-house. Building, governing, and iterating on AI at the same time is exactly what an implementation partner is for.
The AI decisions finance and advisory leaders are working through right now
The firms moving fastest made the right calls early. These are the calls.
- 01
Where does AI create the most value in our firm?
Back- and middle-office work leads for a reason; compliance, reporting, and reconciliation are high-volume, measurable, and low-fiduciary-risk. The front-office wave, research support and client engagement, follows. The right first workflow depends on where your billable and operations hours actually go.
- 02
Build, buy, or partner?
Vendor tools move quickly and custom builds fit your workflows and your book exactly. 87% of firms rely on established closed-source models on trusted platforms, per EY, and 62% prefer a hybrid of vendor AI and internal customization. Most teams need a clear view of which approach fits which use case before committing.
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How do we keep a human on every regulated and fiduciary decision?
Investment recommendations and compliance sign-offs carry fiduciary and regulatory weight. The firms that scale defined, up front, exactly where AI drafts and where a licensed professional decides, with the record to prove it.
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How do we govern AI without slowing everything down?
SEC, FINRA, and SOC 2 are the floor. Governance built as a foundation is what makes scaling possible. Phos AI Labs builds it in from day one.
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When do we move from pilot to production?
Gartner projects that by 2030, agentic AI will make at least 15% of daily finance decisions and 70% of finance functions will use AI for real-time work. The firms that get there are the ones that defined the boundary, redesigned the workflow, and named an owner.
Where AI fits in a finance or advisory firm
From the research desk to the compliance queue, these are the analytical and administrative workflows delivering measurable time back right now. Every one keeps a licensed professional on the decision.
Client reporting and review prep
Assembles portfolio data, performance, and talking points into a review packet drafted for the advisor. Cuts prep time before every client meeting without touching the advice itself.
Meeting notes and CRM updates
Captures the client meeting, drafts the follow-up, and updates the CRM, so advisors stop losing an hour a day to admin and nothing falls through the cracks.
Compliance and disclosure drafting
Drafts surveillance summaries, disclosure language, and regulatory correspondence from your policies and the record. A licensed compliance officer reviews, approves, and owns every filing.
Reconciliation and document extraction
Reads statements, custodial data, and account documents and reconciles them into your systems, flagging only the exceptions for a person to resolve.
RFP and proposal drafting
Assembles RFP responses and new-business proposals from your prior work and approved language, so your team answers more opportunities without rebuilding every document.
Client communications and Q&A
Drafts responses to routine client questions and deflects status requests, so licensed staff spend their time on planning conversations and relationships.
Company knowledge for advisors and operations
Years of product docs, planning playbooks, and compliance policies live in inboxes and shared drives. A grounded AI knowledge system makes them answerable in plain language, in real time, for anyone on the team.
AI prepares:
- Investment and market research synthesized, sourced, and ready to review.
- Client reports and review packets drafted from your own data.
- Compliance and disclosure drafts assembled for a licensed reviewer.
Licensed professionals decide:
- Autonomous investment decisions or trades.
- Unsupervised financial advice to clients.
- Final compliance or regulatory sign-off by the model.
What actually happens once you start?
The canonical Phos AI Labs arc, with the fiduciary boundary built into step one: AI Readiness Audit, then AI Foundation, then AI Implementation. You decide how far to go.
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We set the boundary first (AI Readiness Audit).
Before anyone touches a model, we define exactly where AI drafts and where a licensed professional decides, keep client data inside a compliant environment, and write the human review and recordkeeping into the workflow. We map where your billable and operations hours actually go and rank the workflows by value and readiness. The standalone audit runs 2 weeks; a full multi-department audit runs 3 to 6 weeks.
- 02
We build where the burden is worst (AI Foundation).
Usually research support, reporting, or compliance drafting first; the highest-volume, lowest-fiduciary-risk work. The right models on the right data posture, wired into your systems where it helps, with a licensed professional approving every output that carries a recommendation or a filing.
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We train the team and measure, then compound (AI Implementation).
Each role learns where AI fits their day. We track the hours returned to clients, the reporting turnaround, the compliance cycle time, and we move to the next workflow. Phos AI Labs stays embedded as your stack and the rules change.
For you if:
- You're a wealth or asset manager, RIA, advisory firm, or finance team feeling analytical and administrative overload.
- Research, reporting, or compliance paperwork is your bottleneck.
- You'll keep a licensed professional on every recommendation and sign-off.
Not for you if:
- You want AI making investment decisions or executing trades on its own.
- You want AI giving unsupervised financial advice to clients.
- You can't keep client data inside a compliant environment.
What does responsible AI in finance actually require?
Security stops attacks. Compliance satisfies a regulator. Governance decides what is approved before either is tested. In a fiduciary, regulated business, all three have to be right before anything ships.
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A licensed professional on every regulated and fiduciary decision.
AI drafts, synthesizes, and reconciles. Investment recommendations, advice, and compliance sign-offs stay with a licensed person, with the reasoning and the record captured.
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Client data stays in your environment.
Client PII, portfolio data, and any material non-public information do not leave a compliant boundary or reach a public model. The most common real-world leak is staff pasting client or deal data into consumer chatbots, which a governed rollout removes.
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SEC, FINRA, and recordkeeping, by design.
Supervision, books-and-records, and disclosure obligations are built into the architecture from day one, with the audit trail a regulator expects, not added at the compliance review.
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SOC 2.
Every system Phos AI Labs deploys is built to move your path to certification forward.
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Human oversight, by design.
Generative models are probabilistic and can produce confident, wrong answers. Every output that carries fiduciary, regulatory, or client risk passes through a licensed professional. The system drafts and assembles; the person decides and signs.
What you get from a Phos AI Labs finance engagement
Every engagement produces something your team owns, understands, and can run from day one.
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AI Readiness Report.
Where AI belongs in your firm, ranked by value and sequenced by readiness, with the workflows worth automating and the decisions that stay human.
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Compliance and governance framework.
Your AI use mapped against SEC, FINRA, and SOC 2; supervision, recordkeeping, audit trails, and a runbook that stays current as tools and rules change.
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Built and deployed systems.
Research support, reporting, compliance drafting, or a knowledge base. Live, tested, and adopted by your team before we leave.
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Team training and enablement.
Your advisors, analysts, and operations staff trained on the tools they use daily, built around your workflows and your compliance requirements.
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A governance owner and runbook.
Who owns AI governance inside your firm, and the documentation that keeps it running as models and regulations evolve.
Why Phos AI Labs over a generalist consultant or building it in-house?
As a Claude (Anthropic) Partner and Select OpenAI Partner with 400+ builds behind the team, Phos AI Labs brings the analytical-workflow knowledge, compliance depth, and delivery experience to ship finance AI that stays in production and keeps a licensed professional on every regulated call.
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We build the systems we govern.
Most AI governance advice comes from people who have never shipped in a regulated environment. Phos AI Labs ships systems into production with recordkeeping, audit trails, and review gates built in. We govern from the inside because we know where things break.
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Past the audit.
The audit is where we start. We find the highest-value research and administrative workflows, build the systems that absorb them, and stay embedded as they improve. We ship what we recommend.
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The hire you can't make.
A finance AI strategist, an implementation architect, a compliance specialist, and an enablement lead, working as one team, without the headcount, the six-month ramp, or the $250K+ senior-hire cost.
How much does finance AI consulting cost?
Every engagement is scoped on a call, priced by the size of your firm, and structured so each phase funds the next.
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AI Readiness Audit
from $10,000 fixedThe starting point. We map your workflows, identify where AI creates real value, and deliver a prioritized roadmap with governance and the fiduciary boundary built in. 2 weeks standalone, 3 to 6 weeks for a full multi-department audit.
Explore the audit -
Phase 1 Build
from $15,000 /mo.The first production systems: research support, reporting, compliance drafting, or a knowledge base. Built, deployed, and adopted.
Explore AI Foundation -
Embedded AI Department
up to $50,000 /mo.Phos AI Labs as your finance AI team: strategy, implementation, governance, and iteration as you grow.
Explore AI Consulting
Products
- 01
Nexus, the Private AI Workspace
A secure AI environment for your advisors, analysts, and operations teams, with client data kept inside your boundary. From $500/mo per company, plus tokens.
Explore Nexus → - 02
AI Employees
Autonomous agents handling complete administrative workflows end to end, like reconciliation or reporting prep. $2,500/mo per role, all-inclusive.
Explore AI Employees →
Every engagement starts by finding where current spend, on manual research, rekeyed reporting, and compliance rework, can be redirected into systems that compound. The AI Readiness Audit finds that budget before we ask you for new budget.
Finance AI in production
Real systems, real workflows, real results.
AI in finance and advisory, answered
What is AI for finance and advisory firms?
It's the use of AI on research, documentation, reporting, reconciliation, compliance drafting, and client communication, with every investment recommendation, fiduciary decision, and regulatory sign-off left to a licensed professional. Phos AI Labs builds and embeds those systems inside a compliant environment so the paperwork stops eating billable time.
What is the best first use of AI in a finance or advisory firm?
Research synthesis, client-reporting prep, or compliance drafting. All are high-volume, document-heavy, and reviewed by a person, so they return billable time immediately and carry no fiduciary risk. Back-office wins tend to come before front-office ones.
Can AI make investment decisions or give financial advice?
No. Generative models are probabilistic and can produce confident, wrong answers, and these are fiduciary, regulated moments. AI drafts research, assembles reports, and reconciles data. A licensed professional owns the recommendation, the advice, and the trade.
Is AI safe to use with client and portfolio data?
Only inside a compliant environment with data kept out of consumer tools, and with the recordkeeping SEC and FINRA expect. Most real-world risk comes from staff using unmanaged chatbots, which a governed rollout prevents. Phos AI Labs sets that boundary before any system goes live.
How do we stay compliant with SEC and FINRA?
Every regulated output keeps a licensed reviewer, supervision, and a books-and-records trail, so any advice or filing can be explained and defended. Phos AI Labs builds supervision and recordkeeping into the workflow from the start, not after the compliance review.
Do we need to connect AI to our custodian or portfolio system first?
No. The fastest wins read documents and draft alongside your existing systems, which needs little integration. Deeper custodial and portfolio-system connections come later, once the first workflows prove out.
Will AI replace our advisors or analysts?
No. When AI absorbs research grunt work and reporting admin, your people spend more time on judgment, planning, and client relationships. The evidence points to augmentation.
How much does finance AI consulting cost, and how long does it take?
The AI Readiness Audit starts at $10,000 and runs 2 to 6 weeks depending on scope. A first production system typically takes one to three months from kickoff to live. A full embedded program runs on a quarterly roadmap with systems shipping continuously.
Keep going
- 01
AI Consulting
AI consulting that starts where your team already is. Phos AI Labs audits where AI belongs, builds the highest-value systems, and embeds as your AI team. Audit from $10K.
Explore → - 02
AI Governance
AI governance is the set of rules, access controls, and review steps that decide who can use AI, on what data, and how it gets shipped, installed inside a company's own tools and data.
Explore → - 03
Nexus, the Private AI Workspace
Nexus is a private, company-owned AI workspace grounded in your business knowledge. Rolls out in a couple of weeks. From $500/mo, priced by company.
Explore → - 04
AI Employees
An AI Employee is a trained digital worker that runs your recurring work inside your own tools. Rolls out in 3 to 4 weeks. From $2,500/mo per role.
Explore → - 05
AI Readiness Scorecard
Two free tools to benchmark your AI readiness: a 10-step scorecard and a 3-minute voice audit. Personalized priorities, no sales call required.
Explore →