AI consulting for small business, with a plan before you build

It is a fixed-scope engagement that tells a small business what to build with AI before anything gets built. Nuevexa assesses your readiness, identifies and scores every viable use case, recommends the tools that fit, models the ROI, and sequences the first 90 days. It ends in four documents rather than a deployment.

It is for businesses with 10 to 200 staff that want to use AI but have no agreed plan for where to start. That includes teams exploring AI for the first time, teams whose earlier automation or AI projects did not deliver, and leaders weighing conflicting vendor advice.

Three weeks from kickoff to delivery. The scope and the timeline are fixed before the engagement starts, so the findings do not change the price or push the date.

Scope and price are agreed before the engagement starts, and both are fixed. A strategy call is enough to confirm the engagement fits and to set the scope.

You receive and keep four named outputs: an AI Readiness Report covering your stack, data quality and process maturity; an Automation Opportunity Map scoring every use case against ROI, feasibility and complexity; an independent vendor and tool recommendation with the rationale for each choice; and a 90-day implementation plan. Any accounts set up for later builds are registered to you.

We evaluate LLM foundations such as OpenAI and Anthropic, automation platforms such as n8n, Make and Zapier, and CRMs such as HubSpot, Salesforce and Pipedrive. The recommendation is independent of any vendor relationship, so it is based on fit with your context rather than a sales pitch.

You decide who builds it, and you are not obliged to build with us. The plan stands on its own whether Nuevexa builds it, your own team does, or another partner picks it up. If we build it, the first build is fixed-scope and usually takes 2 to 4 weeks, with an optional managed plan after go-live.

Because builds made in the wrong order cost more than a plan. Teams often start with the flashy application instead of the high-ROI, low-complexity process that would fund everything after it, and those builds create dependencies that slow every later one. Getting the sequence right on paper is far cheaper than resequencing in production.

Usually, yes. Knowing which applications are not worth building is as valuable as knowing which are, and scoring against ROI, feasibility and complexity often changes the order rather than the list.

No. AI built on undefined or inconsistently executed processes inherits those problems and amplifies them at speed, so the readiness assessment surfaces them first. That is what the assessment is for.