We advise, design, build, and run data platforms, AI models, and sensor systems for companies and public-sector teams across Thailand.
From a single sensor network to a regional data platform, we cover the full stack so you are never handed off between vendors mid-project.
Consulting, analysis, design, development, and operations for large-scale data systems: Data Engineering, Data Analytics, Business Intelligence, and decision-support systems for business.
The foundation layer: if data is scattered, wrong, or too slow, everything on top of it wobbles. We build the pipelines and the dashboards first.
Consulting, design, development, and services in AI (artificial intelligence), Machine Learning, mathematical models, forecasting, simulation, and optimization.
Where data turns into prediction and recommendation. We pick the model to fit the question, not the question to fit the model.
Design, development, deployment, service, and maintenance of software, applications, information systems, cloud systems, digital platforms, and Software as a Service (SaaS).
The delivery vehicle for everything else. We build the app, the platform, or the SaaS product, and keep it running.
Research and development of technology, innovation, digital products, models, and automated systems.
For clients who need something that does not exist yet. We prototype, prove it, then industrialize it.
Consulting, study, analysis, and development in water resources, hydrology, hydraulics, water management, drainage, flooding, drought, climate, and forecasting systems.
A domain where poor data carries real cost. We’ve built the satellite-based reservoir models and inflow forecasts that hydropower and water-management operators run day to day. See Track record below.
Study, analysis, and development of GIS systems, remote sensing, satellite data, and spatial analytics.
Everything has a location. We make location usable: maps, imagery, and spatial models that feed the rest of the platform.
Design, development, deployment, and service of measurement systems, IoT sensor telemetry, situation-monitoring systems, and decision-support systems.
The edge of the data graph. We install what measures the world, then pipe it cleanly into the platform and the dashboards.
Consulting services, training, knowledge transfer, and the preparation of research or studies related to the company’s activities.
Capability building, not just delivery. We teach your team to run what we built, and we produce the studies your board or regulator needs.
Buying, selling, leasing, importing, exporting, and procuring equipment, software, computer systems, measuring tools, and hardware/software related to AI, Machine Learning, Data Analytics, and high-performance servers.
Sometimes the fastest path is buying the right gear and standing it up correctly. We source and integrate, not just advise.
Most engagements do not fit a single line item. Here is how we usually combine the nine scopes into the systems our clients actually run.
The most common engagement: clean up the data, build the dashboards the business actually uses, then layer a forecasting model on top when the question becomes “what happens next”.
For operations that need to see what is happening now: sensors in the field, telemetry into the platform, and a live view, plus alerts when a reading crosses the line you set.
Where our water domain meets our data and AI work: hydrological and hydraulic modeling feeding forecasts for floods, drought, and water management, with the systems to act on them.
For clients who need the wider picture: GIS systems, remote sensing, satellite data processing, and spatial analytics, often feeding planning and monitoring workflows.
For clients ready to productize: design, build, deploy, and operate a digital platform or SaaS product, including the cloud, the integrations, and the maintenance that keeps it alive.
When the bottleneck is the gear: sourcing, integrating, and standing up the hardware, servers, and software needed to run AI, ML, and data analytics workloads at scale.
Data infrastructure, AI platforms and applied research in water and remote sensing: experience that connects engineering foundations with working systems.
Selected technical experience in designing, building and operating data servers, cloud infrastructure, processing pipelines and applications. The focus is on the systems and methods, without identifying individuals or organizations.
Experience designing and building data infrastructure, including database servers, cloud environments and containerized services. The work spans PostgreSQL, MySQL and ClickHouse deployments, compute and storage planning, and connecting databases to processing and application layers. Architecture and technology choices balance workload performance, operational cost and long-term maintainability.
Database servers • Cloud infrastructure • Docker • Compute & storage
Built and maintained high-volume data infrastructure, automated cloud-based extraction and loading, and developed bidirectional mappings between source and target databases. Experience covers batch and streaming ingestion patterns, ETL/ELT pipelines and reusable processing utilities, with root-cause analysis to address data-quality issues and operational bottlenecks.
ETL/ELT • Batch & streaming • Cloud automation • Data integrity
Experience with AI aggregator platforms, API and model integrations, model deployment and LLM orchestration. The work connects AI services with data infrastructure and internal tools, supported by provider evaluation and integration planning. Platform decisions consider deployment requirements, interoperability and ongoing compute costs.
AI integration • APIs • Model deployment • LLM orchestration
Experience delivering internal data applications, analytics portals, administrative web tools and microservices that connect processing pipelines with users. Hands-on proofs of concept compare database engines for query latency, memory use and cost-performance. Multi-cloud evaluation and infrastructure-cost tracking inform technology selection and resource optimization.
Data applications • Microservices • POC benchmarking • Cloud cost optimization
Applied hydrology, satellite analysis and operational systems from our water and remote-sensing practice. Specific project clients are not named.
We co-developed a method that uses a satellite-derived moisture index to constrain a semi-distributed rainfall-runoff model in nested tropical catchments, improving both accuracy and the physical realism of the model across 32 sub-catchments. Published in Hydrology and Earth System Sciences (2023).
Remote sensing • Rainfall-runoff modeling • Peer-reviewed
We validated seven global satellite evapotranspiration products against water-balance and satellite gravity (GRACE) data across 172 river sub-basins, identifying the product best suited to water resources management in the region. Published in Journal of Hydrology: Regional Studies (2020).
Remote sensing • Water balance • Peer-reviewed
For a transboundary hydropower operator, we built a method to track upstream reservoir storage from Sentinel-2 and Landsat imagery: water-body detection plus a DEM-derived elevation-storage curve, cross-checked against two independent monitoring services and used to extend forecast lead time on releases the operator does not otherwise see coming.
GIS • Remote sensing • Satellite hydrology
We built a semi-distributed rainfall-runoff and reservoir-routing model driven by satellite rainfall, with a bias-correction step that roughly halved next-day forecast error and beat the operator’s existing benchmark model by double digits on weekly inflow declarations.
Hydrology • AI/ML forecasting • Operational modeling
A cloud hydrological database, live dashboards, and threshold alerts over SMS, email, and chat, across a multi-station hydropower fleet, with a mobile app for field engineers and direct ingestion of global weather-forecast data for the next 14 days.
IoT telemetry • Dashboards • Cloud platform
A hydrodynamic and water-quality model of a major river system, simulating dissolved oxygen and organic-load levels under population-growth and wastewater scenarios two decades out, benchmarked against national water-quality standards across multiple river reaches.
Water quality modeling • Scenario analysis • Regulatory benchmarking
We are built for clients who need more than a vendor: a partner that stays through design, build, deployment, and the years of operation that follow.
Nexflow is a consulting, design, development, and operations company for data-intensive systems. We do not sell packaged software off the shelf. We build the specific platform, model, or sensor network a client needs, then help run it. Our work sits at the intersection of data engineering, analytics, AI/ML, spatial technology, and connected devices.
Our water and remote-sensing practice builds on years of applied hydrology research, including peer-reviewed publications on satellite-based rainfall-runoff modeling and evapotranspiration, carried into production systems for hydropower and water-management operators. See Track record.
Most engagements move through four phases, and we are happy to join at any of them, not only at the start.
We reply within two business days. If the problem is in scope, we suggest a first conversation or a short scoping piece, never a pitch deck.