AI Advisory
AI, in
order.
Strategy for private equity, finance, law, healthcare and other firms where mistakes are expensive. We show you where to start, put the first project into production, and keep costs tied to results.
Florida · New York · California
- 01 Assess
- 02 Plan
- 03 Build
- 04 Train
The idea
Sequence is the strategy.
An assessment comes before a plan so the plan is about your data and your rules rather than a vendor's demo. The plan comes before the build so the first thing built is the one with a clear measure and an owner. Training runs alongside the build so the result survives the handoff and does not depend on the people who built it. Firms that skip a step tend to buy tools that sit unused.
What we do
The four steps run in order.
- 01
AI Readiness Assessment
An inventory of your systems, data, current AI use and vendor terms, with interviews across departments. The result is a readiness report and a prioritized 90-day pilot proposal.
What you get A written readiness report and a prioritized 90-day pilot proposal.
- 02
Strategy and Roadmap
Workflow selection with a success measure for each, model and vendor choices checked against your compliance rules, and build-or-buy decisions. Every item gets a budget, an owner and a date.
What you get A roadmap the leadership team can approve and a pilot scope ready to start.
- 03
Implementation
The scoped pilot built and put into production: automation, document processing, retrieval over your own documents, or agents with approval gates. Cost controls and monitoring are part of the build.
What you get A workflow in production with before-and-after measures, documentation and a handoff.
- 04
Training and Change Management
Role-based training, a written AI use policy, an internal champion program and shared prompt libraries. Runs alongside Build or on its own.
What you get A team that uses what was built, and a policy the firm can show a client or regulator.
Where we work
We work in industries with rules.
- Private Equity Deal screening, diligence and portfolio reporting without crossing confidentiality walls.
- Finance Intake, reconciliation and policy answers under GLBA, SOX and model risk guidance.
- Investing Research, RFPs and client reporting inside the marketing rule and books-and-records obligations.
- Law Review, drafting and intake under privilege rules and bar guidance on generative AI.
- Healthcare Documentation and administrative work with PHI kept out of consumer tools.
- Manufacturing Quoting, maintenance and quality documentation with the plant floor kept separate.
- Biotech Literature, submissions and lab documentation under Part 11 and GxP validation.
- Defense Proposals, CMMC documentation and manual search with CUI on approved systems only.
- Real Estate Leases, diligence and tenant communication with no AI in a tenant or buyer decision.
- Hospitality Guest communication and back office work with payment and guest data protected.
Approach
What happens, in order.
- 01 Assess AI Readiness Assessment
- 02 Plan Strategy and Roadmap
- 03 Build Implementation
- 04 Train Training and Change Management
Find out what to do first.
Thirty yes or no questions take about three minutes. Your score updates as you go and comes with a plain recommendation, and you see it without giving an email.
Take the readiness checklistQuestions
Six questions, answered straight.
What does Silver Buttonwood do?
We do advisory and implementation, in that order. The work starts with an assessment of your systems, data and rules, then a roadmap the leadership team can approve, then the first pilot built into production, with training for the team that will use it. A firm can stop after the assessment or the roadmap with a usable document in hand.
Do you build software or recommend tools?
We do both. An existing tool comes first when one fits the workflow and your compliance rules. A custom build happens when no faster option exists, and it is scoped to the one workflow in the pilot.
Will our data end up in a public model?
No. Every assessment reviews vendor terms and moves the firm onto enterprise plans where data is excluded from training. For controlled data such as PHI, MNPI or CUI, the plan uses private or on-premise models.
How long until something is in production?
That depends on the firm and the workflow, so we do not publish a schedule. The pilot proposal that closes the assessment names the first workflow and the date it goes live. After that, every item on the roadmap carries its own date.
What size of company is the right fit?
Firms from SMBs to large enterprises. The scope changes with the size of the firm, and the sequence does not.
What does it cost?
Pricing depends on the project and the budget. Each proposal carries the price for its scope, and costs stay tied to results.
Put your AI work in order.
One conversation tells you whether to start with an assessment or go straight to a roadmap.