AI consulting built for growing businesses, not enterprises
Most well-known AI consulting firms are built for large enterprises. Their engagements are sized for big budgets, long discovery phases and executive steering committees. That model suits a global company rolling out AI across dozens of departments. It's a poor fit for a small company that wants to stop keying invoices by hand.
We're an AI consulting company for US small and mid-sized businesses that need a working AI system, not a slide deck. We find where AI will pay off, write it down in a roadmap you keep, then build, launch and support what we recommend. Unlike a firm that hands over recommendations and walks away, the team that advises you is the team that builds.
Our clients are usually owners, operators and department heads at companies with a clear business problem, some data to work with and no in-house AI team. Many have tried a general AI tool, got mixed results, and want to know what a proper system would look like for their business.
Here's what to expect. It starts with a free 30-minute consultation, and within 24 hours you get a written AI roadmap that's yours to keep, whether or not you work with us. The work is hands-on: we look at how tasks actually get done, talk to the people who do them, and check ideas against your real data during scoping, before anyone commits to a full build.
Why this matters
Buying AI tools without a plan is how businesses end up paying for software nobody uses. A few hours of honest advice up front tells you which tasks are worth automating, which aren't, and what a realistic result looks like. Because we have to build what we recommend, our advice stays practical.
What an AI consulting engagement covers
An engagement produces work you can act on. The free roadmap gives you the first ranking of ideas. The deeper work below, on your data and systems, happens during paid scoping.
- AI readiness assessment. We look at how a business function runs today, what data it produces, which systems it uses and who does what. The goal is an honest answer to one question: is this area ready for AI, and if not, what has to change first?
- Use case prioritization. Most businesses have more AI ideas than budget. We rank them by effort and payoff, so you start with the one most likely to pay back and skip the ones that sound good but won't.
- Build vs buy recommendation. For each use case we check whether a tool you already pay for, or an off-the-shelf product, can do the job. Buying is often cheaper than building, and we'll say so. Custom work makes sense when your process or your data is what sets you apart.
- Data and integration audit. We review where your data lives, how clean it is, and how an AI system would connect to your CRM, ERP, help desk or other tools. This is where most AI projects succeed or fail, so we check it early.
- Implementation roadmap. You get a written plan: which use cases to tackle, in what order, what each one needs from your team, and what would drive its cost.
- Risk and guardrails review. For each use case we note where the AI could get something wrong, what a person should check, and what data it must never see.
This isn't strategy work that ends with a report. When you're ready, the roadmap leads straight into a build.
Where AI consulting fits before automation, agents or chatbots
For most businesses, consulting is the first step. You know AI could help, but you're not sure whether the answer is an agent, an automated workflow, a chatbot or a change to software you already own. A short assessment sorts that out before you spend money on the wrong build.
Once the roadmap is clear, the work usually moves into one of our build services:
- AI agent development: agents that take on work needing judgment, such as reviewing documents or triaging requests, with a person approving the decisions that matter.
- AI automation services: workflows that connect the tools you already run and remove manual steps, like copying data from one system to another.
- AI chatbot development: chatbots that answer customers or staff from your own knowledge and hand over to a person when they should.
- AI app and software development: custom AI apps and platforms, including AI features inside a product you already sell.
If you already know what you need, go straight to those pages. If you don't, start here.
Our AI consulting process: assessment, roadmap, build, support
The process has four steps, and you decide at each one whether to go on.
- Assessment. We start with a free 30-minute consultation about how your business runs, where your team loses time and what you've already tried. From there we focus on one business function, such as finance, sales or customer support, and look at the steps, the people and the data involved.
- Roadmap. After the consultation you get a written roadmap listing the best AI opportunities we found, ranked by effort and payoff, with the approach we'd take for each and what would drive its cost. For the idea you want to pursue, a short paid scoping phase reviews your data, systems and processes in detail and designs the solution with you.
- Build. We build what the roadmap recommends, in stages you approve. You see working software in regular demos, and we test the AI on your real data before it goes live.
- Support. After launch we monitor accuracy, costs and usage, fix issues, and keep improving the system as your team uses it.
Nothing in this process locks you in. You can stop after the roadmap and take it to another team or to your own developers. Many clients use it to plan their budget or brief their staff.
Generative AI and AI implementation consulting
Generative AI consulting is about finding the places where models that read and write text actually help a small business. The useful cases tend to be ordinary ones:
- Content drafting: first drafts of proposals, product descriptions, emails and reports that a person reviews before they go out.
- Internal search: staff ask questions in plain language and get answers from your own documents, policies and past work, with links to the source.
- Customer support: answering routine questions from your help articles and routing the rest to your team.
- Summarization: turning long calls, contracts, tickets or research into short summaries people can act on.
We're just as clear about where generative AI doesn't fit yet, such as decisions that need a guaranteed right answer with no person checking it.
AI implementation consulting is the day-to-day work of getting from an idea to a working system. First, data readiness: is your data complete, current and reachable? Then vendor and model selection: which model or product fits your accuracy, cost and privacy needs? Then integration, which is most of what AI integration consulting means: connecting the system to the CRM, ERP, help desk or accounting software you already use, so nobody has to switch tools. We're model-agnostic and recommend OpenAI, Claude or open-source models based on the job, not on a vendor relationship.
In practice, implementation consulting often catches the small problems that stall projects: customer records split across two systems, documents stored as scans with no text, an API your vendor charges extra for, or a process that works differently at each location. Finding these before the build keeps the plan honest.
How we're different from large AI consulting firms
Large consultancies do valuable work, and for some companies they're the right choice. Here's how our approach differs from a large consultancy.
- We build what we recommend. At many large firms, the strategy team hands its recommendations to a separate systems integrator. With us, one team has written the roadmap and built the software on 20+ AI products, so nothing gets lost in a handoff.
- We price by project. Instead of billing by the hour or by phase, we give you a fixed price for the agreed scope once scoping is done, so you know the full cost before we build.
- You talk directly with the people designing and building your software.
- We size plans for smaller businesses. Our recommendations assume a small team, a limited budget and the tools you already want to keep using.
To be fair to the other side: if you need board-level AI governance strategy across a multinational, a large global consultancy is the better call. We're the right fit when you want a practical plan and a team that will build it.
Projects that started with an assessment
Each of these projects began with an assessment phase, where we mapped how the work was done and what data was available, before we built anything. The full case studies cover the problem, what we built and the results.
- Invoice automation for a mid-sized manufacturer. We started by shadowing the finance team through a month-end close and cataloguing the invoice formats in use. The platform we then built extracts and validates invoice data and cross-checks it against the ERP, cutting processing time from hours to seconds. Read the AI-powered invoice automation case study.
- Hiring software for an HR tech company. The first step was a bias audit of historical hiring data and new evaluation rubrics designed with the client's talent team. That work shaped a platform for resume ranking and automated voice interviews. See the recruitment platform case study.
- A research assistant for an enterprise pharma consulting firm. We began with a data audit to decide which sources to include and how to judge answer quality. The result is an assistant that gives consultants cited answers from curated datasets and documents. Read the pharma research assistant case study.
AI consulting pricing and how to get started
The consultation and written roadmap are free. Scoping is a short paid phase, sized by how many systems and how much data the chosen use case involves. After scoping you get a fixed price and timeline for the build.
What drives the cost of a build: how many steps and systems it touches, the state of your data, which models it uses, how much testing the AI needs, and your security and compliance requirements. See how we price custom AI projects, or read our realistic AI project cost breakdown for more on what shapes a budget.
To get started, book a free consultation. Tell us how your business runs and where the time goes, and we'll follow up with your written roadmap.
What to bring to the first call: a short description of the process you want to improve, the tools it runs on, and who does the work today. You don't need a technical brief.
What you get
- A written AI roadmap that's yours to keep
- A detailed solution design and data review from paid scoping
- Code and documentation handed over if you build your own team
Related services
AI Automation Services
Workflows that connect your tools and remove manual steps.
AI Agent Development
Agents that take on work needing judgment, with a human in the loop.
AI Chatbot Development
Custom chatbots trained on your knowledge, with human handover.
AI App & Software Development
Custom AI apps, platforms and products, built and supported.
Related case studies
AI-Powered Invoice Automation
Manufacturing · Avg. invoice processing time: 4 hrs → 12 sec
Read the case studyIntelligent Recruitment Platform
Human Resources · Time-to-first-interview: 5 days → same day
Read the case studyAgentic RAG Pharma Research Assistant
Pharma · Research query time: 2 hrs → 8 sec
Read the case study