AI consulting — from people who ship AI, not slide decks

The AI consulting industry has a product problem: its product is the deck. A strategist interviews your team for two weeks, delivers sixty slides about "transformation," and is gone before anyone has to make a single thing work. Six months later the slides are in a drawer and the only AI in the building is whatever your staff quietly paste into a free chatbot.

We come at this from the other side. We're an engineering shop that ships AI features — retrieval-backed assistants, lead-qualification flows, content pipelines — inside the same Next.js stack we build websites and webapps on. When we advise on AI, the advice is shaped by what survives contact with production: latency, hallucination rates, token costs at real volume, and the unglamorous state of most companies' data.

What AI consulting means in our hands

The audit starts with your workflows, not the technology. We map where hours actually go and where errors actually happen — intake, quoting, support, reporting — and only then ask which of those a model can genuinely absorb. Use cases get ranked by payback and risk, not by demo appeal.

"You don't need AI for this" is a real deliverable. A meaningful share of what gets pitched as AI is a cron job, a validation rule, or a SaaS setting nobody turned on. When the honest answer is boring automation, the roadmap says so, with the cost difference in writing. We'd rather lose a build than sell you one you don't need.

Vendor-neutral by construction. We resell nothing and carry no reseller margin, so the build-vs-buy analysis can be honest: what the vendor charges at your projected volume, what a build costs to run and maintain, and where the crossover sits.

What a typical engagement includes

• AI opportunity audit — structured interviews plus workflow mapping, ending in a ranked shortlist of candidate use cases
• Feasibility and build-vs-buy analysis for the top candidates, with real cost modelling
• Data-readiness assessment — where your data lives, how clean it is, and what has to be fixed before any model can help
• Roadmap with honest cost/benefit — sequenced, budgeted, with explicit kill criteria for every item
• Vendor and model selection — a decision matrix, not a logo slide, priced at your volume
• Team enablement — working sessions with the people who'll actually use the tools: prompt patterns, guardrails, and a clear policy on what never gets pasted into a chatbot

How we evaluate models and vendors

We're model-agnostic across Claude, GPT, Gemini, and open-weight options. Four criteria, in order: accuracy on your task (measured with a small eval set built from your real examples, not vendor benchmarks), latency, cost at production volume, and privacy / data-residency fit. For prototypes we reach for the Vercel AI SDK, retrieval on Postgres + pgvector, and evals before demos — if a recommendation can't survive a fifty-example eval, it doesn't go in the roadmap. And if the roadmap ends in a build, we can be the ones who build it — or hand the spec to your team.

What this looks like in practice

Two typical engagement shapes:

The opportunity audit (2–3 weeks). A service business drowning in repetitive inbox, intake, or quoting work wants to know what AI can actually take off its plate. We interview the team, map the workflows, and deliver a ranked roadmap. Sometimes the top item is an LLM-backed intake assistant; sometimes it's plain automation with no model in it. Either way you get the reasoning and the numbers, and a plan you can execute with us or with anyone else.

The feasibility spike (3–5 weeks). A company already sold on a specific idea — or being pitched hard by a vendor — wants proof before committing. We build a thin working prototype against a sample of your real data, run an eval, model the cost at production volume, and deliver a build-vs-buy memo. It's the cheap way to avoid an expensive mistake in either direction.

Pricing

AI consulting is scoped to the project. An opportunity audit for a five-person firm and a feasibility spike for a two-hundred-seat rollout are different animals, and pretending one price list covers both is how slide-deck consulting happens. Tell us what you're weighing and we'll come back with a fixed-price scope — contact us for a quote.

Ready to find out what's real?

Same operating rhythm as our build work: a reply within four business hours, a 30-minute call within two days, a fixed-price scope in writing. And if the honest answer on that call is that you don't need us, that's exactly what you'll hear — free.

Start an AI Consulting engagement → — or book a 30-min call