aiplusmo delivers custom AI software development, AI strategy and consulting, deployment of machine learning models, data engineering, and ongoing model support. We help organizations assess AI readiness, design solutions that match business needs, and implement systems that integrate with existing IT infrastructure.

Project timelines vary by scope. Initial discovery and proof of concept can take 2–6 weeks. Building a production-ready model and integration usually spans 2–6 months depending on data complexity and required compliance. We provide a clear timeline after the discovery phase and work in iterative milestones to deliver value early.

We work across sectors including retail, management, manufacturing, logistics, healthcare operations, and service businesses. Our focus is on practical AI that improves operational efficiency, reduces repetitive tasks, and enhances decision-making within industry constraints.

Data protection is part of our development lifecycle. We implement role-based access controls, data anonymization where appropriate, encryption at rest and in transit, and follow best practices for secure deployments. For regulated data we design workflows that minimize exposure and support client-specific compliance requirements.

Yes. We provide remote and on-site collaboration as needed, including workshops and installation support at client locations in Thailand. Our office address in Nonthaburi is available for scheduled meetings and demonstrations.

Pricing depends on project scope, data readiness, and integration complexity. We offer packaged services for short engagements and custom proposals for larger programs. After an initial consultation, we provide a transparent proposal with scope, milestones and cost estimates.

Yes. We specialize in integrating models into existing applications, APIs, and workflows. Our engineers design connectors and APIs to ensure models operate reliably within your ecosystem and support deployment strategies like containerization or serverless endpoints.

We offer monitoring, model retraining schedules, incident response, and performance tuning. Support packages can be tailored to your needs — from periodic health checks to a managed service with SLAs for uptime and response times.

Success is defined jointly with the client through measurable KPIs such as accuracy improvements, time saved, reduced manual processing, or cost per transaction. We track those metrics through deployment and provide regular reports to assess impact and next steps.

AI adoption often requires adjustments in workflows and staff roles. We emphasize minimal disruption: starting with pilots that demonstrate practical benefits, training key users, and creating clear handover documentation to help teams adopt new tools effectively.

We work with a broad stack including Python, TensorFlow, PyTorch, ONNX, Kubernetes, Docker, AWS, GCP, Azure, and modern data tools. Technology choices are driven by project requirements, scalability needs and client preferences.

Start by contacting us through the form or calling +66945430552. We will schedule a discovery meeting to understand your objectives, review available data, and outline a practical roadmap with clear milestones and costs.