FIELD NOTES · WEALTH MANAGEMENT · AI
ILLUSTRATIVE RECORD
Build a firm that knows what to do with AI.
Last Mile works alongside wealth management teams to develop practical AI skill, redesign real workflows, and build what’s missing.
It starts with one real workflow — RMD season, annual reviews, whatever strains — followed with the people carrying it.
Your staff build practical AI skill on that live work, not in a training room.
When the evidence calls for an automation or an internal tool, we build it.
the firm keeps itEverything is documented and handed over. Your firm owns it after we leave.
Eighteen years inside wealth management. Five years working hands-on with AI.
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The same technology lands differently in every practice.
Last Mile works inside one real workflow with the people carrying it. We follow the handoffs, decisions, workarounds, and controls before deciding what should change.
Five conditions that reshape one workflow
- Systems
- Ownership
- Controls
- Client behavior
- Practice habits
RMD work changes across the year.
Some practices schedule distributions throughout the year, while others handle a rush each December. Custodians may drive the reminders or leave the practice to chase every client, and ownership can shift between advisors, service teams, and operations.
Last Mile works alongside the people carrying the work, follows the workflow as it runs, and learns where the strain comes from before recommending a change.
The answer might be stronger AI skill, a small automation, or a custom tool. We’ll build what’s missing.
Illustrative workflow topology
Beginning of year · Spring
Summer
Fall
Holiday seasonDecember concentration
Systematic monthly plans and automatic beginning-of-year draws, cleared early
Summer lull
The remaining list is worked down between the quarterly passes
Custodian cutoff
Q1
Q2
Q3
Q4 · Review before release
Exception: client response needed
Exception: client response needed
Exception: client response needed
Missed entirely, surfaced at tax time
Automated custodian pull
Balances and RMD amounts, no one re-keys them
Quarterly inventory pass
Who has cleared and who has not, then follow-up, so nothing stays missed
Continuous confirmation
Each clear is logged as it happens, so reconciliation runs all year
Routed to a named owner
Owner
Advisor
Service team
Operations
When does the work concentrate?
Annual reviews aren’t annual.
The meeting may happen once a year, but the work accumulates between reviews: client changes, planning decisions, open commitments, and context spread across the practice. Last Mile learns how that context becomes preparation, conversation, and follow-through before changing the workflow around it.
Annual review context trace
Twelve months between reviews
Client changes
Open commitments
Planning decisions
Practice context
Preparation
Owner
Conversation
Follow-through
How Last Mile works.
The engagement begins by following one live workflow with the people carrying it. What changes depends on the ownership, information, approvals, systems, and sequence causing strain. Practical AI skill develops in that same operating context. When the evidence supports an automation or internal tool, we build it. Each change is documented and transferred so the firm can maintain it. The work can continue into the next consequential workflow when useful.
Engagement trace
Last Mile still holds the work
1
Observe
2
Change
3
Build and teach when warranted
Conditional on the evidence
Owned by the firm
4
Transfer
5
Continue when useful
Next consequential workflow
Last Mile upskills and builds automations where your friction lives — and we train your staff so it doesn’t come back.
Eighteen years inside wealth management and five years of hands-on work with AI.
Last Mile brings experience across advisory work, wealth management operations, technology evaluation, and the systems firms use to plan, report, document, and serve clients. Since 2021, that experience has developed alongside continuous work with AI, including application development, workflow automation, retrieval-augmented systems, deep research and data synthesis, and local model deployment.
That background shapes the practical questions behind each engagement: where the work begins, which system holds the relevant information, what staff can reasonably review, and what the firm can maintain after the engagement ends.
Start with one workflow.
The first engagement begins with one consequential workflow rather than a broad transformation program. Last Mile learns how the work moves, identifies the decisions and constraints shaping it, and determines what combination of workflow change, practical AI skill, automation, or internal tooling is warranted.
Start a conversationCurious? Tell us about the work you want changed, and we’ll show you what it could look like.