Strategic Finance, Configured

AI in FP&A and Strategic Finance has been stuck in pilot.
We get it into production.

AMW configures the data connections, financial models, and Claude Skills your team needs to do real analytical work inside Claude. Your team gets a working analytical environment they use every day, without the year-long internal build.

Schedule a Conversation with Adam See the work →
Example Output - User inputs a simple prompt and gets detailed financial analysis in minutes.
Sample analytical briefing: client portfolio ranked by net contribution after overhead allocation, showing seven clients with revenue, gross margin, and profitability metrics.

Output from a configured AMW environment. See the full demo →

The Problem

AI can do real strategic finance work.
The infrastructure is what's missing.

What used to take a week can now be done in minutes. Drop a dataset into Claude, ask a question, and you'll get back analysis that holds up. A lot of finance people are seeing it. Just check your LinkedIn feed.

But almost no one has done the harder thing: connecting all your core datasets, financial models, and analysis approach into one contained environment, so that the AI can take any difficult financial question, independently query the right data sources, run the analysis, validate the numbers, and assemble a CEO-ready output.

The constraint isn't the data. It isn't the skill of the team. It isn't the capability of the model.

It's the infrastructure that connects them.

That gap is what stops AI from compounding inside a strategic finance function. And it's what AMW is built to close.

What We Build

A configured analytical environment,
built around your team's actual work.

AMW builds and validates a working analytical environment inside your company's Claude instance. We set up secure data connections to your source systems, encode your financial models, build custom Claude Agents and Skills for the analytical work your team does, and validate everything end-to-end against your data.

Your team accesses it through Claude Chat, Cowork, and Claude in Excel. Hard analytical questions get fast, defensible answers. The output isn't a chat transcript. It's a polished, CEO-ready HTML artifact with the analysis laid out, the numbers tied to source, and the recommendation written for an executive audience. Delivered in minutes instead of days.

Connected
Your data. Secured, live, and accessible by custom agents.
No more hunting and pecking for data. No more waiting on the BI team for an extract. Once configured, custom agents independently deduce what data is needed for the question at hand, retrieve it from your source systems, validate it, and hand it off to other agents for analysis.
Encoded
Your financial logic, embedded.
Your forecast methodology, budget structure, cash flow model, unit economics, what-if scenario models, and other custom models are encoded into the environment, so the analytical work follows your team's standards rather than generic logic.
Validated
Tick-and-tie discipline, built in.
Every connection, every model, every Skill is tested end-to-end against your real data before handoff. Every number in every answer traces back to an authoritative source. No making up figures. No invented attribution. If the answer can't be tied back to your data and your models, it doesn't ship.
What It Answers

The kinds of questions
your team should be able to answer in minutes.

If you're a CFO or have ever led an FP&A or Strategic Finance team, you know the kind of rapid fire questions the business must answer to run effectively. They're complex, they're interrelated, and they require pulling together data from multiple systems and running it through your team's financial logic to get an answer you can trust. A configured environment turns hard analytical questions into fast, defensible answers. Not because the AI is smarter, but because it has been built around your data, your models, and the way your team actually thinks about the business.

"
What's our customer concentration risk if revenue growth from our top three accounts continues to outpace the rest of the portfolio?
"
Model the P&L impact of raising prices 8% on our bottom-quartile margin segment, assuming 15% churn. How does that compare to a smaller increase with lower churn risk?
"
What's driving the variance in gross margin between Q3 budget and Q3 actuals? Decompose it by business unit, by product line, and by mix versus rate.
"
If we close the acquisition at the current LOI terms, what does the consolidated P&L and cash position look like through 2027 under base, upside, and downside scenarios?
"
Which of our SaaS cohorts are tracking ahead of LTV expectations and which are tracking behind? What does that imply for next year's CAC budget by channel?
"
Our largest customer is asking for a 12% volume discount in exchange for a three-year extension. What does that do to deal-level economics, contribution margin, and consolidated EBITDA, and what's the breakeven on the extension length?
"
If headcount growth comes in 20% above plan and revenue comes in 10% below, when do we breach our covenants, and what are the two or three biggest cost levers available before we get there?
"
Build me a board-ready summary of Q2 performance against budget, with the three things going well, the three things to flag, and a recommendation on whether to update full-year guidance.

Every answer traces back to your source data and your team's own financial models. No invented numbers, no generic logic.

See the Work

Real analytical work,
produced by a configured environment.

The briefings below were produced by AMW's configured environment for Brightline Creative Group, a fictional company with synthetic financial data. Each one was generated from a single prompt and reflects the kind of analytical work a strategic finance leader actually needs.

Briefing 03
Portfolio Briefing
Full client portfolio review of revenue, gross margin, and profitability after overhead allocation. Addresses concentration risk and the economics of individual accounts.
Briefing 04
Repricing Analysis
Selective rate increase scenario modeled against the 2026 P&L and cash position, with churn risk overlay and side-by-side comparison of stay-vs-churn outcomes.
Briefing 05
Creative Director Hiring Decision
Full-time hire versus freelance arrangement. P&L impact across base, upside, and downside scenarios, with cash runway analysis and a timing recommendation.
Briefing 06
Cash Recovery Briefing
LOC paydown trajectory under each forecast scenario, cash runway sensitivity, and the two or three biggest levers available to accelerate recovery.
Explore the Full Demo

Synthetic data only. Brightline Creative Group is a fictional company.

How It Deploys

Built inside your Claude.
Owned and used by your team.

AMW configures the analytical environment inside your company's Claude instance. Your team accesses it the same way they access anything else in Claude: through Chat, Cowork, and Claude in Excel. There's no separate interface to log into, no new tool for the team to adopt, and no data leaving your Claude environment.

Engagements typically run 2 to 4 weeks from kickoff to a working environment in your team's hands. AMW builds, validates, and hands off, and remains available for ongoing configuration as your needs evolve.

Prerequisite
AMW is built for companies on Claude Team or Claude Enterprise.
The configured environment is deployed inside your existing Claude instance. If your team isn't on Claude Team or Enterprise yet, the right first step is getting your company set up there, and we're happy to talk through what that looks like.
Why I Built This

A note from Adam Ware.

I spent the last fifteen years inside fast-moving technology companies in senior finance roles, including a decade at Amazon and stints at GoPuff and GeoComply. Most recently I was Head of Finance at GeoComply, where I owned the strategic finance function end to end.

The pattern I kept seeing, in every company I worked at and every CFO conversation I had, was the same. The strategic finance function was being asked to deliver faster, deeper analytical work. Board reporting, scenario modeling, variance analysis, M&A support. And there was never enough time, never enough analyst capacity, never quite the right infrastructure to make it all run.

When AI started getting genuinely good, I watched the LinkedIn feed fill up with finance people running impressive one-off analyses. Take a dataset, drop it into Claude, get back a useful answer. I was doing it too. But I noticed almost nobody was doing the harder thing: building an environment where the AI is connected to the actual systems and models a finance team relies on, so that the work compounds instead of restarting every time.

I left GeoComply in early 2026 to go build that environment as a service. AMW is the result. I configure the data connections, encode the financial models, build the custom Claude Skills, and validate every number against source. Every engagement I do, I do personally. What you're buying is the combination of senior finance judgment and an operator who has spent the last year on the cutting edge of AI for strategic finance.

If you're seeing the same gap I am, between what AI can do and what your team is actually getting out of it, I'd like to talk.

Adam Ware
Founder, AMW Analytical Systems

Head of Finance, GeoComply
Senior finance leader at Amazon and GoPuff
Strategic finance and FP&A across $100M to $50B revenue businesses
Seattle, Washington
Adam Ware
Get in Touch

Let's talk.

A first conversation is a substantive discussion about where your team is on AI adoption, what's working, what isn't, and where a configured environment could move the needle.

Schedule a conversation with Adam
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[email protected]
(206) 398-9719

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