GradicentAI Consulting helps companies build, validate, and deploy AI/ML solutions that actually work in production — not just in notebooks.
We cover the full stack of AI/ML work — from strategy to deployment — so you do not have to stitch together multiple vendors.
We help you figure out what to build — and whether it is worth building. Strategy, model selection, feasibility assessment, and technical roadmaps grounded in your actual data.
Strategy →Got an idea but need to prove it works? We build fast, focused proofs of concept that give you something real to show stakeholders — in weeks, not months.
Fast delivery →Industrial sensors generate enormous signal. We help you extract the part that matters — anomaly detection, predictive maintenance, and real-time quality monitoring on live data streams.
Industrial data →Clean data is the foundation of everything. We design and build robust pipelines that take your raw, messy source data and turn it into something models can actually learn from.
Robust pipelines →A model that lives only in a notebook is not a solution. We take models to production — with monitoring, retraining triggers, and the infrastructure to keep them working over time.
Production ready →Sometimes you need more than a model — you need the application around it. We build custom tools, dashboards, and integrations that put AI in the hands of the people who need it.
Full stack →We spend real time understanding your problem — the data you have, the decisions you need to make, and what success looks like for your team. No assumptions.
We prototype quickly, show you working results early, and iterate based on what we learn. No six-month discovery phases before you see anything real.
We do not hand off a model and disappear. We help you put it into production, train your team, and make sure it keeps working as your data changes.
We have hands-on experience with messy, high-volume sensor data from manufacturing and energy environments — the kind of data that most ML tutorials skip over. We know what breaks in production.
Our proofs of concept are designed to be shown to stakeholders. Clear outputs, explainable results, and a story that makes the business case for you — not just a Jupyter notebook.
We will not push a framework because we are certified in it. We pick what fits your problem — a simple regression, a foundation model, or something in between.
We can talk to your data engineers and your business leaders in the same meeting. Translating between the two is half the job — and we are genuinely good at it.
You work directly with the people building your solution — no account managers in the middle, no handoffs to junior staff. Every project gets senior attention from day one.
Quality control, anomaly detection, predictive maintenance — we work directly with sensor and line data in real production environments.
From lubricant health monitoring to operational efficiency — AI/ML applied to the continuous time-series data energy systems generate.
Customer propensity modelling, purchase prediction, churn analysis — turning transaction data into actionable commercial intelligence.
If you have data and a decision worth improving, we are interested. The domain changes — the rigour does not.
GradicentAI Consulting was founded with one belief: the gap between a working AI model and a deployed AI solution is where most consulting firms lose the plot.
We are a lean team of data scientists, ML engineers, and software developers who have built and shipped AI solutions across manufacturing, energy, and commercial domains. We do not sell strategy decks. We build things.
Tell us what you are working on. We will tell you honestly whether we can help — and what that would look like.
Start a conversation → No pitch deck. No commitment. Just a conversation.