An AI Consulting Company That Hands You a Buildable Plan, Not a Slide Deck

Already know exactly what you want built? Skip the strategy phase and go straight to our AI development company page. This page is for the step before that: deciding what to build, in what order, and whether to build at all.

The most expensive AI mistake isn't a failed model. It's six months and a serious budget spent building the wrong thing well: a chatbot nobody uses, a prediction engine trained on data that was never clean enough, a pilot solving a problem that was never the bottleneck. Post-mortems on stalled AI projects trace back to the same root causes (unclear business case, unready data, no owner), all decisions that went wrong before development started.

That's the phase an AI consulting company exists for: the boring, decisive questions. Which of your processes actually benefit from AI, and by how much, in currency? Is your data good enough, and if not, what's the shortest fix? Buy an off-the-shelf tool, orchestrate existing models, or build custom? Who's accountable when the model is wrong?

MONA answers those questions with an unusual bias: honesty enforced by proximity. Our consultants sit in the same company as the 200+ staff who would build the system, so a recommendation that can't survive implementation embarrasses the people down the hall. When the honest answer is "this doesn't need AI, it needs a better process," we say that too. A decade of building CRMs, ERPs, and management systems across 14,000+ projects delivered has taught us what technology adoption looks like when it works, and when it quietly dies.

Our AI consulting services cover everything between "we should do something with AI" and the first line of production code. Each one produces a concrete, decision-ready artifact: not observations, decisions.

AI Readiness Assessment

A structured audit of the three things AI projects live or die on: your data (where it lives, how clean it is, who can access it), your systems (what integrates, what's locked in legacy tools), and your team (who will own, use, and supervise the AI). Output: a readiness scorecard with the specific gaps to close before building.

Use-Case Discovery & ROI Prioritization

We interview the people who do the work, map where hours and errors actually accumulate, and turn the wishlist into a ranked portfolio: each use case scored for financial impact, feasibility against your real data, implementation cost, and risk. The top items are typically unglamorous and immediately profitable; the moonshots are parked with a clear trigger for revisiting them.

Data Foundation & Architecture Review

Most companies don't have an AI problem; they have a data problem wearing an AI costume. We review your sources, pipelines, and quality, then design the foundation your chosen use cases require: what to consolidate, what to clean, what to start capturing today so next year's models have history to learn from.

Build vs. Buy vs. Orchestrate

For each use case, three honest options: buy an existing product, orchestrate current AI tools into your workflows, or build custom. We model each path's cost, time-to-value, lock-in risk, and ceiling. Sometimes the right answer is a low-cost subscription. When it is, we say so and save you the build.

AI Strategy & Roadmap

The synthesis: a sequenced 6-18 month plan that opens with a quick, visible win, layers in higher-value systems as your data foundation matures, and defines the metric each phase must hit before the next one funds. Every item carries an owner, a success metric, and an estimate reviewed by the engineers who would build it.

AI Governance, Risk & Responsible AI

The unglamorous layer that keeps AI out of the headlines for the wrong reasons: acceptable-use policy for staff, human-in-the-loop checkpoints wherever errors carry cost, data privacy boundaries (what may and may not touch third-party APIs), vendor and model risk, and monitoring obligations. Scaled to your size: a working document people follow, not a 90-page binder nobody opens.

Two families of AI, two different consulting questions, and a lot of budget wasted confusing them.

Generative AI Consulting

Generative AI (LLMs like GPT, Claude, and Gemini) is the fastest-moving layer and the easiest to misuse. Our generative AI consulting separates durable value from demo theater: which workflows genuinely benefit from language models (document drafting, multilingual support, knowledge retrieval over your contracts and manuals), what grounding they need to answer from your data instead of hallucinating, where outputs stay behind human review, and how to architect for model portability so a provider's price change never becomes your emergency.

Machine Learning Consulting

Classical machine learning (forecasting, churn prediction, lead scoring, pricing, anomaly detection) is older, less hyped, and often higher-ROI. It's also where honest machine learning consulting matters most, because feasibility depends entirely on your historical data. We audit whether your volume, quality, and history can support the accuracy you need; when they can't, we design the collection plan and stage the use case for when the data exists.

The deliverable across both: a clear-eyed map of which family (or neither) fits each use case, before an eager vendor decides for you.

The AI gold rush has minted a lot of AI consulting firms, and they fail in two opposite ways. Big strategy consultancies deliver beautiful analysis at eye-watering rates, then leave. And the development vendor you hand the deck to says "this isn't how we'd build it." Solo "AI strategists" sell recycled frameworks with no engineering depth behind them. Either way you pay twice: once for the plan, again to translate it into something buildable.

When you evaluate AI consulting firms, four questions expose the difference fast:

• Have they built what they recommend? A consultant who has never lived through deployment hands you a roadmap that ignores everything deployment teaches.
• Is the deliverable decision-ready? "Explore opportunities in generative AI" is not advice. Ranked use cases with costs, metrics, and owners is.
• Can the same firm execute? Not because you must hire them for the build, but a firm that could build its own plan has no room to hide behind vagueness.
• Do they ever say no? A consultancy that finds an AI use case in every corner of your business is selling, not consulting.

MONA passes all four for a structural reason, not a rhetorical one: we're a software development company of 10+ years that added AI to a working engineering practice, not a consultancy that added "AI" to its letterhead.

1. Free Strategy Call. Thirty minutes to understand your business, your AI ambitions, and whether consulting is even the right next step. If your case is clear-cut, we'll say so and point you straight to scoping the build.
2. Discovery & Stakeholder Interviews. We talk to the people who do the work, not just the people who commissioned the project. The real bottlenecks live in the workflows, not the org chart.
3. Data & Systems Audit. Hands-on review of your actual data and integration surface. This is where engineer-consultants earn their keep: we read schemas and APIs, not just slide templates.
4. Use-Case Ranking Workshop. We present the scored portfolio, pressure-test it with your team, and agree the sequence together, so the roadmap has internal owners before it has a cover page.
5. Roadmap & Governance Delivery. Sequenced roadmap, architecture direction, build-vs-buy calls, budget ranges, governance framework, success metrics: written to be executable by us, your team, or any competent vendor.
6. Execution Support (Optional). Most clients continue into delivery with the MONA teams the roadmap was designed around: custom systems with our AI development company, operational workflows with our AI automation agency. Some execute in-house with our consultants on call. Both are wins.

Traditional AI strategy consulting is priced so only enterprises can afford to think before they build. Mid-market companies are expected to guess. Vietnam's engineering economics change that: MONA delivers senior, engineering-grade AI consulting at a fraction of US and Western European rates, so the entire strategy phase costs less than the first month of a misdirected build.

• Consultants with commit histories. Your strategy is shaped by people from a 200+ staff organization who ship software for a living: CRM, ERP, web platforms, AI systems.
• Pattern knowledge from 14,000+ projects delivered. A decade of building the exact back-office systems AI now plugs into means we've usually seen your workflow before, edge cases included.
• One roof from idea to production. Strategy, custom development, automation, and cloud hosting inside one group. No hand-off tax, no "that's the other vendor's layer."
• GMT+7, English-proficient, PM-led. Overlap with European mornings and US evenings; documentation discipline proven with demanding markets including Japan.
• No-lock-in deliverables. Every roadmap is written so you can execute it without us. We'd rather earn the build phase than contractually capture it.

A roadmap is only worth what gets built from it. Depending on your prioritized use cases, execution flows to the right team:

• Custom AI systems: LLM applications, RAG knowledge bases, computer vision, ML models, our AI development company
• Workflow and operations automation with existing tools and models, our AI automation agency
• Autonomous, tool-using agents that plan and act across your systems, our AI agent development team
• The software around the AI: platforms, portals, and integrations, our custom software development practice

Because the consultants and builders are one company, nothing is lost between plan and product: the engineer who challenged a feasibility assumption in week two is still there when it gets tested in month four.

• AI Strategy Call (free). A conversation, not a commitment: we map where you are and recommend the lightest useful next step.
• AI Readiness Assessment (fixed fee). The data-systems-team audit with a scorecard and gap list. The best first purchase for most companies.
• Full Strategy Engagement (fixed fee). Readiness assessment plus use-case portfolio, build-vs-buy analysis, sequenced roadmap, and governance framework.
• Advisory Retainer. Ongoing access to our consultants as you execute: reviewing vendor proposals, unblocking decisions, re-ranking the portfolio as the model landscape shifts.

Every engagement is fixed-scope with a written deliverable defined before you commit.