Building an AI Co-Strategist for a Six-Person Spirits Company
We built an internal tool that knows our business in granular detail and scores every idea against weighted strategic objectives. It's a co-strategist with an objective point of view.
Build Log
We recently finished building a tool that has quietly become one of the most useful things in our business. It started as a scratchpad for ideas and innovation, somewhere to dump the constant stream of "what if we tried..." thoughts that accumulate when you're running a small company in a fast-moving space. It turned into something considerably more interesting.
The tool knows the drinks industry in detail. More importantly, it knows Asterley Bros in granular detail: our capacity, our skills, our team, our strengths, our history, our preferences, and our tools. When we throw an idea at it, the AI doesn't just nod along. It reviews, rates, and provides detailed feedback based on a set of criteria that actually matter to a business our size.
What the system evaluates, and why those dimensions matter
Every idea that goes into the tool gets scored across multiple dimensions. Not abstract ones. Practical ones tied directly to whether a six-person company can actually execute on something and generate value from it.
The evaluation criteria:
Capability match. Can we actually do this with the skills, equipment, and production capacity we have right now? Not aspirationally. Right now.
Strategic alignment. Does this idea move us toward the objectives we've set for the business this quarter or this year? A great idea that doesn't align with current strategy is still a great idea, but it might need to wait.
Operating channel fit. Does this work within the channels we already operate in, or does it require us to build new distribution, new partnerships, new infrastructure?
Team strengths. Where does our team's expertise actually sit? An idea that plays to what we're already good at has a fundamentally different risk profile to one that requires us to learn something new while executing.
Customer preferences. What do we know about what our customers value, how they buy, what they respond to? An innovation that doesn't connect to existing customer insight is a guess, not a strategy.
Cost efficiencies and savings. What does this cost to implement, and does it reduce costs elsewhere? For a small business, cash flow isn't a line item. It's the oxygen supply.
ROI and revenue potential. What's the realistic return, and over what timeframe? Not the optimistic scenario. The realistic one.
The tool processes all of this against our actual data and returns a scored evaluation with written feedback explaining its reasoning. According to McKinsey's 2025 State of AI survey, 64% of organisations report that AI is enabling their innovation, but fewer than 40% see enterprise-level profit impact. The gap, in our experience, is between using AI to generate ideas and using AI to evaluate them against reality. Most businesses have plenty of ideas. What they lack is a fast, objective way to sort the good ones from the expensive ones.
The configurable weighting system
Here's where it gets genuinely powerful. We set our own strategic objectives to guide how the tool weights its evaluations. Currently, revenue growth is weighted most heavily, because that's where the business needs to focus right now. But the system adapts.
If we shifted our priority to sustainability, the tool would score environmental impact and resource efficiency higher, potentially surfacing opportunities that a revenue-first lens would rank lower. If marketing and outreach became the primary objective, the system would emphasise brand visibility, customer acquisition cost, and market penetration over pure financial return.
| Priority weighting | What scores highest | What gets deprioritised |
|---|---|---|
| Revenue growth (current) | ROI, revenue potential, cost efficiency | Long-term brand building, experimental formats |
| Brand building | Customer alignment, channel fit, market positioning | Short-term financial return |
| Sustainability | Resource efficiency, supply chain impact, waste reduction | Revenue maximisation, rapid scaling |
| Innovation/R&D | Technical novelty, team learning, market differentiation | Immediate ROI, operational simplicity |
This isn't a fixed algorithm. It's a strategic lens that we control. The AI adapts its objectivity to our subjectivity about what matters most right now, and that combination is where the real value sits.
When the tool pushes back
The most useful moments aren't when the tool validates our excitement. They're when it pushes back.
Ideas that seemed great on first pass regularly get flagged as carrying too much risk, too much workload, or too many unknowns. The system doesn't kill them outright. It rates them as less viable in the short term and suggests revisiting when conditions change. Some ideas that scored poorly six months ago might score well once capacity frees up or a new team member joins.
This is a huge valuable tool that gives you objective strategic guidance in almost instant feedback.
The near-instant feedback matters. In a large company, a new idea might go through weeks of internal review, committee meetings, feasibility studies. For a small team, the temptation is to skip all that and just try things, because the alternative is bureaucracy that doesn't suit the pace of a growing business. The AI co-strategist sits in between: fast enough that it doesn't slow us down, rigorous enough that it catches things we'd otherwise miss in our enthusiasm.
Forbes reported that by the end of 2026, more than 80% of small businesses will be using AI for marketing. But the strategic layer, using AI to evaluate business decisions rather than just execute on them, is where far fewer companies have ventured. That's the gap we're working in, both at Asterley Bros and through Absolution Labs with clients.
What the tool doesn't do
It doesn't make decisions for us. It doesn't know what it feels like to stand in front of a buyer and pitch a new product. It doesn't understand the relationship we've built with a particular supplier over five years, or why we'd take a slightly worse deal to keep working with someone we trust. It doesn't have taste.
What it does is provide an objective point of view that counterbalances the natural optimism founders have for their own ideas. Every entrepreneur overestimates the upside of something they're excited about. Having a system that dispassionately evaluates capability, cost, alignment, and risk doesn't replace instinct. It sharpens it.
A co-strategist with an objective point of view. That's what we built. And for a team of six competing in a market shaped by companies with hundreds of people and proper advisory boards, that objective perspective is worth more than most of the tools we've invested in.
Frequently asked questions
What is an AI co-strategist for a small business?
An AI co-strategist is a system trained on a company's specific data (capacity, team skills, financials, production history, customer preferences) that evaluates business ideas and innovations against weighted strategic objectives. It provides objective scoring and feedback, acting as a strategic advisory layer for founders who don't have large teams of experts and consultants.
How does multi-criteria AI scoring work for business decisions?
The system evaluates ideas across multiple dimensions: capability match, strategic alignment, operating channel fit, team strengths, customer preferences, cost efficiencies, potential savings, ROI, and revenue potential. Each criterion is scored based on the business's actual data. Strategic objectives can be weighted differently depending on current priorities.
Can AI push back on business ideas?
Yes. A well-built AI co-strategist will flag ideas that carry excessive risk, workload, or unknowns, rating them as less viable in the short term. This provides objective feedback that counterbalances the natural enthusiasm founders have for their own ideas.
What data does an AI strategy tool need from a small drinks company?
At minimum: production capacity, team skills and headcount, financial position, product history, customer preferences, supply chain relationships, and current strategic objectives. For a spirits company, this also includes botanical knowledge, batch records, regulatory requirements, and distribution channel details.
Robert Berry is co-founder of Asterley Bros, a London-based premium aperitivo company, and Absolution Labs, an AI automation consultancy for drinks businesses. He makes vermouth by day and builds AI systems in the margins.