AI Strategy & Consulting
A clear, ROI-first AI roadmap, where to apply AI, what to build, and what to ignore.
AI without the hype.
Most AI initiatives stall because they start with tools instead of outcomes. We start with your P&L: we find the workflows where AI moves a real number, then sequence a roadmap you can actually ship.
- AI opportunity audit across your operations
- Use-case scoring by ROI and feasibility
- Build-vs-buy and model selection guidance
- Data readiness and governance review
- Phased implementation roadmap
- Risk, compliance, and guardrail planning
Who it's for.
- Leaders who know AI matters but not where to start
- Teams burned by a failed pilot
- Companies sitting on data they don't use
- Orgs that need a plan the board will fund
See if AI Strategy & Consulting is the right move for your team.
Request a free quoteWe Build the AI Roadmap, Then Run It
Some engagements stop at a slide deck; ours continues into implementation. Our senior team works inside your operation to design the AI strategy, then we build the systems and run them in production. We map where Claude with Salesforce Agentforce, OpenAI GPT, and open models like Llama, Hermes, and Mistral each fit your stack, and we own the rollout from first pilot to live deployment.
We run quarterly roadmap reviews against live production metrics, so the strategy keeps moving with your revenue, not the slide deck.
- We audit your data, tools, and workflows, then design a model and architecture plan you can actually ship
- We choose the right mix of Claude, Agentforce, GPT, and open models per use case instead of forcing one vendor
- We stand up governance, security, and cost controls so AI scales without surprises
- We stay on as the team that builds and operates the roadmap, not a consultant who leaves after the deck
A roadmap, not a slide deck.
You leave with a prioritized, costed plan, the use cases, the sequence, the metrics, and the guardrails, ready to execute.
Questions, answered.
You get a prioritized roadmap of AI use cases scored on business value, feasibility, and cost, plus a clear build-vs-buy call for each one and a sequenced rollout plan with rough budgets. We also flag the use cases to ignore, since saying no to low-ROI ideas is half the value. The deliverable is decision-ready, not a slide deck that sits on a shelf, so your team can start executing the week it lands.
A focused roadmap typically runs three to six weeks depending on the number of departments and systems involved. We start with stakeholder interviews and a review of your data, tools, and existing workflows, then map and score candidate use cases, and finish with a prioritized plan and ROI model. For example, a mid-market team might come out with a 12-use-case backlog where the top three (a support triage agent, a sales research assistant, and an internal knowledge search) are scoped to ship first.
Every use case is scored against real business impact, data readiness, integration effort, and ongoing run cost, then ranked so the high-value, low-friction work surfaces first. We are model-agnostic across Claude, GPT, and open models like Llama and Mistral, so the recommendation is driven by your problem and not by a vendor relationship. For example, we will often steer a client away from a flashy custom model toward a simpler retrieval setup or an off-the-shelf tool when the math does not justify the build.
We do both. The strategy stands on its own, but NYFTY is a team that builds, manages, and runs the work, so we can carry the priority use cases straight into implementation using tools, frameworks, and platforms like LangGraph, CrewAI, n8n, and Salesforce Agentforce. You are never handed a plan with no one to execute it, and you are free to take the roadmap to your own team or another vendor if you prefer.
No. Data and team readiness are part of what we assess, and the roadmap accounts for your actual starting point rather than an ideal one. If your data is messy or siloed, that becomes a sequenced prerequisite with its own effort estimate, and we will identify quick-win use cases that can ship on the data you already have while the bigger foundations get built. The goal is momentum and ROI early, not a year of cleanup before anything ships.