Twelve years of expertise. Trapped in Outlook and file servers.
One operator with AI systems that analyzed more than a decade of published materials for a $14B wealth advisory firm. Institutional knowledge made searchable, reports automated, governance built in.
Work-Smart builds AI infrastructure for financial services: consolidate institutional data from email and spreadsheets, automate quarterly reporting, deploy private AI without compliance risk. Fixed-fee builds and monthly retainers. You own everything.
Fixed-Fee Builds•Production-Ready Systems•Zero Public AI. Private Only
Here's what I see in every financial services firm I talk to.
Your critical data lives in Outlook.
Not Google Drive. Not a database. Outlook. Twelve years of institutional knowledge sits in individual inboxes: fund performance, investor communications, regulatory guidance, the playbooks that built your reputation. When someone resigns, their inbox becomes archaeological evidence. Knowledge that took a decade to build vanishes in a week.
Your quarterly reporting process is killing your timeline.
Every quarter, your team loses two full weeks to manual work. Pulling numbers from the accounting platform. Reconciling them against the other systems. Rebuilding presentations from scratch. Then audit prep hits: hundreds of pages of regulatory documents, compliance updates, and fund prospectuses. Someone has to flag every change by hand because nothing is searchable.
Your team is using ChatGPT. The public version. Without governance.
Fund data, investor details, and regulatory strategy are getting pasted into a system that trains on every conversation and keeps it forever. That is shadow AI. That is compliance risk. That is the thing you should be losing sleep over.
You haven't solved any of this.
Every option you looked at failed a real test. The consulting firm quoted $400K for a strategy deck. The off-the-shelf BI tool does not fit how you actually work. The SaaS platform locks you into licensing forever. The real issue is that you need AI infrastructure built for financial services, not sold to financial services.
Here's what changed.
A $14 Billion Wealth Advisory Firm
90% of institutional data in Outlook. Proposal creation took 4 to 8 hours. Leadership had no way to search 12 years of institutional knowledge.
Searchable institutional knowledge layer
More than a decade of documents processed, recurring questions answered, indexed and searchable in seconds. Fund history, investor data, past decisions, strategic playbooks. Available to the entire team. No more asking someone.
Proposal automation
What took 4 to 8 hours now takes minutes. Pulls current fund data, investment performance, market context, investor history, and builds it into a polished presentation automatically.
Command center for leadership
Real-time view of fund performance, portfolio metrics, investor pipeline. The executive team sees what matters without meetings or status updates.
Authority framework for business development
60 content pages targeting the 12 questions prospects and LLMs ask about wealth advisory AI. Roughly a 100x gap closed between branded and non-branded search visibility.
Timeline: 9 months across 3 phases. Result: Authority content produced in the firm's exact institutional voice. 60 authority pages live. 539 existing answers mapped and structured across 10 pillars. The firm shows up when prospects ask AI about their space.
What this looked like in practice
The engagement started as a 6-week AI Visibility project, making 12 years of institutional expertise visible to AI search engines. Conversations with each partner uncovered six operational gaps that had nothing to do with the website: proposals written from scratch, knowledge trapped in email, tools deployed but unconfigured, meeting intelligence disappearing after every call. What began as content became a 9-month Fractional Head of AI engagement spanning data, knowledge, and team enablement. Different starting point, same architecture underneath.
You should talk to me if:
20 to 200 employees and real AI infrastructure needs.
A 50-person family office with $500M AUM is my sweet spot. A 500-person regional bank is not (too many stakeholders).
Your data chaos is your biggest problem.
Fund data, investor history, regulatory documents, institutional knowledge, all real, all critical, all scattered. Once it's consolidated, everything else becomes possible.
Quarterly reporting or compliance cycles killing your timeline.
If 15 days a quarter disappears to manual consolidation, that's a real problem worth a focused build to solve.
Worried about compliance and data security.
You're not going to be the firm that leaked investor data to ChatGPT. You need private AI, not public.
You've been quoted $400K by a consulting firm.
You don't need a 12-person strategy team. You need one person who understands your business, builds the system, and stays to evolve it.
You should not talk to me if:
Your data is already consolidated and your quarterly reporting is fast.
You don't have a specific operational pain point to solve.
You have 1,000+ employees or a highly matrixed organization. (You need an enterprise consulting firm.)
You want to "explore AI" without a clear business outcome.
Three engagement types. Pick based on where you are.
1. The Diagnostic
Fixed-fee diagnostic
Two to four weeks where I map your operation. Your data, your tools, your processes, your team's AI usage. I identify where you're losing time and money. Then I tell you honestly what to build.
This is not a strategy deck. You get a roadmap tied to your operation's reality, not consulting templates.
2. The Build
Fixed-fee build
The implementation. The scope comes from the diagnostic. Data layer. Command center. Private AI. Governance system. First working system ships in 4 to 8 weeks. Full build takes 6 to 12 weeks.
Phase ships → you pay. No surprises. No scope creep.
3. The Retainer
Monthly retainer
After the build ships, most firms move to monthly engagement. System maintenance, 1 to 2 new capabilities monthly, team enablement, governance monitoring, executive reporting.
This is what keeps your AI infrastructure from decaying the day I finish building it.
Four reasons your AI implementation needs a different approach.
Privacy is non-negotiable.
You cannot use public ChatGPT. Every conversation trains on your data, and every investor detail, fund strategy, and compliance decision feeds into a system owned by someone else that keeps logs forever. I build private AI instead. Your data stays inside your system. Zero retention. No training on your information. Your compliance officer approves it because it is actually compliant.
Institutional knowledge is your moat.
Your competitive advantage lives in people's heads. Fund management frameworks. Investor relationships built over 15 years. Market analysis. Investment theses. If someone resigns, does all of that walk out the door with them? I build searchable knowledge systems that preserve what your team has learned. New hires find the playbook. Your team references past decisions. The knowledge stays institutional instead of personal.
Compliance risk is real.
Other industries can move fast. You cannot. Regulatory changes hit your entire operation: IFRS updates, SEC guidance, fund-specific requirements. An AI system built without governance in mind exposes you to all of it. I start with governance. What can the AI touch? What does it log? Where are the human approval steps? That is not slowing you down. That is protecting you.
Your quarterly cycle is a killer.
Every 90 days your whole operation compresses into reporting. Consolidation. Audit prep. Investor communication. It is predictable pain, and it is fixable. I automate the manual parts so your team spends its time on strategy instead of spreadsheets.
Concrete. Specific. Honest.
Cost: Fixed fee, scoped to complexity. You know the exact price before we start.
Discovery
I meet with your leadership, finance team, and operations. I walk through where your data lives (NetSuite, Outlook, folders, spreadsheets), what processes kill your timeline (reporting, compliance, investor communication), what your team is doing with AI right now (shadow AI audit), and what compliance constraints matter.
Analysis
I model out your data flows. Where is the bottleneck? What is costing you time? What is a compliance risk? Then I identify the single system that would change your timeline the most if it were automated and cleaned up.
Recommendations
I deliver the diagnostic. Not a 200-page deck. A concise, specific roadmap: what's broken and why, what system to build first, the timeline, the cost, what gets built in phases. Most diagnostics lead to a build. Some lead to "fix your data governance before you do anything else." I tell you honestly what makes sense.
You've probably thought about this before.
"We already do content marketing. We have podcasts, white papers, thought leadership."
That's exactly the point. You have the intellectual capital, it's just invisible to machines. One wealth advisory firm had more than a decade of documents and a deep podcast library. They appeared in 2 of 10 relevant AI queries. The content existed. The structure didn't.
"Compliance will never approve this."
Everything I produce goes through your compliance review. Most firms already have 15+ years of compliance-approved content sitting in old folders. Reformatting existing approved content is faster than creating new content from scratch.
"Our market is too small for this to matter."
A family office serving ultra-high-net-worth families has a tiny addressable market. But one firm already closed a deal because a prospect found them via ChatGPT, unplanned, before any AI visibility work.
The AI Operating System. Applied to Your Industry
Data Consolidation
Your data does not live in one place. Fund data sits in NetSuite. Investor data sits in Outlook and a spreadsheet. Compliance documents sit in a folder. Playbooks sit in people's heads. I consolidate all of that into a single source of truth. That is the foundation every AI system actually needs. You cannot have a live dashboard without clean data.
Executive Dashboard
A real-time dashboard that answers your critical business questions. Fund performance. Investor pipeline. Compliance status. Asset under management trends. Anything your CEO needs to know, available instantly instead of "let me send you a spreadsheet."
Private AI (Not ChatGPT)
I build private AI instead of letting teams use public ChatGPT. A system trained on your data, your fund history, your investor relationships. Your team asks it questions and gets answers rooted in institutional knowledge, not hallucinations. Zero retention. No training on your information.
Governed Automation
Workflows that run without human intervention, but with complete visibility. Report generation. Compliance updates. Presentation building. Client communication. The automation doesn't guess. It follows rules you define. You see what it did, why it did it, and can adjust the logic anytime.
AI Governance
The layer nobody else emphasizes, and the one you cannot skip. An AI use policy. Shadow AI monitoring. An approved tool list. A data exposure assessment. You are not banning AI. You are controlling it in a way your compliance team can sign off on. Financial services firms that skip this step end up paying for data leakage and remediation later.
A $14 Billion Wealth Advisory Firm
90% of critical institutional data trapped in Outlook. 12 years of fund decisions, investor relationships, portfolio history, all living in individual inboxes. Proposal creation took 4 to 8 hours because every number had to be manually gathered and verified.
More than a decade of documents processed, recurring questions answered, indexed and searchable in seconds. Proposal automation reduced proposal creation from 4 to 8 hours to minutes. 60 authority pages live. Roughly two orders of magnitude between branded and non-branded search visibility. The firm shows up when prospects ask AI about their space.
Read the full case study →Frequently Asked Questions
The diagnostic is a fixed-fee 2-4 week engagement. The build is fixed-fee, scoped from the diagnostic, could be focused report automation or a full foundation. The retainer is a monthly engagement after the build. Everything is milestone-based, you only pay when deliverables ship. The diagnostic shows you the exact build cost before you commit.
Yes. I build on top of your existing systems, not instead of them. The diagnostic will tell us what to connect, what to consolidate, and what to leave alone. I've done this with NetSuite, QuickBooks, custom databases, and Outlook.
Governance is built into every system I deliver. AI use policy. Shadow AI monitoring. Data exposure assessment. Audit trail for every decision the AI makes. I work with your compliance team, not around them. Your audit should actually get easier, not harder.
No. After the system ships, you own it completely. The source code, the data models, the AI integrations, all documented and handed off to your team or whoever you want to manage it. If you go to a retainer, I have access to maintain it. If you're done, it's yours. Clean handoff. No lock-in.
Platforms lock you in. You pay a monthly fee forever and they own your data structure. I build custom systems for your operation. You own what's built. The data is yours. If I get hit by a bus, another engineer can pick it up because it's not proprietary. You're buying a builder and a system, not renting access to someone else's platform.
I could. And I will if that's the honest answer. But most financial services firms I talk to have tried that already. Bought a BI tool, bought a data platform, bought an AI assistant. None of them work because the problem isn't the tool, it's how your data is structured, your processes are designed, and your team is trained. Building fixes the real problem. Tools rarely do.
That's the retainer. A fixed-fee monthly engagement for ongoing AI operations, governance, capability expansion, and team enablement. Most people start with a diagnostic and a build, then move to the retainer when the system is in production. You don't need the retainer during the build, you need it after, when the system needs to evolve with your business.
Yes, if you train it on your language. I extract a communication profile from your existing documents, the way your firm talks about governance, investment philosophy, family enterprise. The AI writes in your voice, using your vocabulary, not generic financial jargon. One firm's profile was 220 lines extracted from more than a decade of published materials.
68% of next-gen ultra-high-net-worth families already use AI tools for financial research. 61% prefer digital-first interaction. The $84 trillion generational wealth transfer is happening now. The firms that show up in ChatGPT and Perplexity when these prospects search will win the next generation. The firms that don't will rely on referrals from a shrinking network.
Most financial services firms start with the diagnostic. The build question answers itself from there.
You've probably tried solving this alone. Or you got quoted something that doesn't make sense. Or you're worried about compliance and you don't know who to trust. The diagnostic answers those questions. Two to four weeks, fixed fee. You come out with a clear roadmap, specific pricing, and honest advice about what makes sense.