Six areas where MintAI builds and runs AI inside your organization, each from a real business problem, governed and controlled.
Agents, data, vision, decision support, knowledge, deployment.
AI agents and workflow automation
The problem
Skilled people spend hours on repetitive, rules-based work that slows the whole organization down.
How we deploy
We build governed AI agents that operate inside your existing processes and systems.
The outcome
Routine work runs reliably, with people in control of approvals and exceptions.
How it works
Agents are scoped to specific tasks and connected to your systems through controlled integrations. Every action can be logged, and sensitive steps route to a human for approval. We design for auditability first, so automation stays accountable as it scales.
Data intelligence and predictive analytics
The problem
Decisions run on fragmented data that lives in different systems and rarely agrees.
How we deploy
We build data intelligence and predictive models on a foundation you can trust.
The outcome
Leaders act on a single, current view instead of stale or conflicting reports.
How it works
We consolidate the data that matters, apply forecasting and pattern models suited to your sector, and surface results where decisions are made. Models are designed to be explainable and reviewable, and they run on infrastructure you control.
Computer vision
The problem
Quality, safety and yield still depend on manual inspection that cannot keep pace with operations.
How we deploy
We deploy computer vision that reads what is happening on the line, in the field or on site.
The outcome
Issues are caught in real time, before they become cost, waste or risk.
How it works
Vision systems are trained on your conditions and integrated with existing cameras and equipment where possible. Detections feed dashboards and alerts, and can trigger governed workflows. Models are designed to run at the edge or in-country, keeping imagery under local control.
Executive and operational decision support
The problem
Executives and operators lack a clear, current picture when they most need to decide.
How we deploy
We build decision cockpits that bring the right signals into one governed view.
The outcome
People at every level see what is happening and what to do next.
How it works
We combine live operational data, forecasts and AI summaries into role-specific views. Each figure is traceable to its source, so trust is built in. The layer is designed to sit on top of the systems you already run.
Governed knowledge assistants
The problem
Institutional knowledge is scattered across documents and systems, and answers are slow to find.
How we deploy
We deploy assistants that answer from approved knowledge, with sources and escalation.
The outcome
People get trusted answers in seconds, and reach a person when knowledge runs out.
How it works
Assistants are permission-aware and cite the source of every answer. When something falls outside approved knowledge, the assistant says so and escalates to a human focal point. This is the category our first product, DOHxai, is built for.
Model deployment and managed AI services
The problem
Promising models stall because there is no secure, in-country way to run them in production.
How we deploy
We deploy and operate models on sovereign infrastructure, as a managed service.
The outcome
AI runs reliably in production, under your governance and inside national borders.
How it works
We handle hosting, orchestration, monitoring and updates so your teams do not have to. Models run on secure GPU infrastructure designed to keep data and compute in-country. You keep control of policy, access and audit throughout.
Build AI capability that remains under your control.
Start with a conversation. We come prepared with a practical view of where AI fits.