BREWER STRATEGIES / AI
Every tool we ship has an AI engine somewhere inside it — reading invoices, drafting outreach, answering customers. Here's the field, in plain English: what each engine is, what it's genuinely good at, and how we decide which one goes into yours.
The engine family we reach for first. Claude is exceptional at careful reading, multi-step reasoning, and following precise instructions — and it comes in tiers, from a fast, inexpensive model for high-volume work to a frontier model for hard judgment calls.
How we use itClaude reads the invoices in our AP automation, powers the fourteen-agent staff in our ops cockpit, and drafts client-ready copy — each task matched to the right tier so quality stays high and costs stay flat.
The engine that made AI a household word. GPT models are strong all-rounders with a huge tooling ecosystem around them, and OpenAI's voice and image models are among the best available.
How we use itWhen a build calls for voice interfaces, image generation, or a capability where OpenAI's ecosystem has the edge, we wire GPT in — often alongside another engine doing the core reasoning.
Google's engine, built to handle enormous amounts of material at once — video, audio, images, and very long documents — and naturally at home inside the Google ecosystem your business may already run on.
How we use itFor tools that live in Gmail, Drive, or Sheets, or that need to digest hours of audio or hundreds of pages in one pass, Gemini is often the practical choice.
Meta's openly released model family. Because the weights are public, Llama can run on infrastructure you control — which matters for strict privacy requirements or very high-volume workloads where per-call pricing hurts.
How we use itWhen a client needs AI that never leaves their infrastructure, or a narrow task run millions of times, an open model like Llama can be the cost-and-privacy answer.
A European lab known for small, fast models that punch far above their size. Mistral offers both open models and a commercial API, and its efficiency makes it attractive for lightweight embedded tasks.
How we use itFor quick classification, routing, and extraction steps inside larger pipelines — places where a small, cheap, fast model does the job perfectly well.
xAI's engine, distinguished by its live connection to the X platform and a rapid release pace. A newer entrant that's improving quickly.
How we use itSparingly today — mainly where live social signal matters. We evaluate every major release, and if Grok becomes the right answer for a job, it goes in the toolbox.
Enterprise-grade engines, wired to your workflow.
A large language model — software trained on enormous amounts of text (and often images and audio) until it can read, write, and reason about new material it's never seen. Your tool sends it a job ("read this invoice, pull out the line items") and gets structured work back in seconds. It's a component inside your tool, the way a database or a payment processor is — you never interact with it directly.
Not the way we build. We use business-tier APIs whose terms exclude your data from training — never consumer chatbot accounts. Your documents are sent for processing, processed, and returned. For clients with stricter requirements, open-weight models can run on infrastructure you control so data never leaves your environment at all.
Whichever fits the job — and often more than one. A single tool might use a fast, inexpensive model to sort and route documents, and a frontier model for the judgment calls. That decision is engineering, not loyalty: we re-evaluate as models improve, and because we host and maintain your tool, upgrades happen behind the scenes without you lifting a finger.
It can, which is why we never build "trust the AI" systems. Every tool we ship is designed with checks: extracted numbers are validated against source documents, prices are compared to a database, and anything uncertain is flagged to a human instead of guessed at. In our AP automation, an invoice outside tolerance doesn't get paid — it gets queued for your approval.
For most tools, surprisingly little — routine document processing typically costs cents. Modest usage is bundled into your flat monthly fee. If your tool becomes a heavy user, we set up a dedicated account in your name with a spending cap, so costs stay visible and yours.
No — the point of a custom tool is that it molds to your business, not the reverse. We build around what you run today: your accounting system, your inbox, your calendar, your spreadsheets. The AI does the tedious middle part your team currently does by hand.
You benefit automatically. Engines improve every few months, and because your tool is hosted and maintained by us, swapping in a better or cheaper model is our job, done behind the scenes. Your tool quietly gets smarter over time — that's a feature of the model, not a new invoice.
Any engine can answer a prompt. The craft is the tool built around it — the checks, the connections, the workflow. That's what we do.