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Overview

Transpara Platform is under development

Welcome to the journey from Visual KPI to the all new Transpara real-time operational intelligence platform. The new platform is already being battle-tested with major customers (let us know if you want to take part), but is also still in development. The documentation will be updated over time as new features are released. Stay tuned for more updates!

The Transpara Platform is a modern, AI-optimized operational intelligence system designed to unify, analyze and visualize data from all your industrial and business systems, without the time, effort and cost of migrating data and manually creating the results. With real-time insights, mobile-ready interfaces, and optional data storage, Transpara empowers organizations to act faster, reduce cost, and stay ahead of performance issues.

What is Transpara?​

The Transpara Platform is a modern, AI-optimized operational intelligence system designed to unify, analyze and visualize data from all your industrial and business systems, without the time, effort and cost of migrating data and manually creating the results. With real-time insights, mobile-ready interfaces, and optional data storage, Transpara empowers organizations to act faster, reduce cost, and stay ahead of performance issues.

The platform works without forced data migration projects, without giving up control of your environment. Transpara runs in your infrastructure (on-premise, in your cloud, or hybrid), connects directly to your existing sources, and leverages AI at your pace and with your choice of models (public frontier models like OpenAI/Anthropic/Google, or locally running models with no outside access like Ollama and others). You can even choose different models for different tasks, but it is always under your control.

Industrial AI for Real-Time Operations​

Most "industrial AI" products fall into two camps. Either they are batch analytics dressed up with an LLM, looking at last week's data and explaining it. Or they are a chat window bolted onto a legacy system. Either way, that is a weak use of AI in industrial operations.

Transpara goes further. It can leverage AI right down to the core of the platform (it was designed from the group up with this in mind), and provide huge benefits in various ways:

  • Onboarding: Building and adjusting your model with you. The Transpara Model Builder turns a company name or URL into a complete operational model in minutes: hierarchy, KPIs, calculations, limits, dashboards, charts, and even geolocation. You can even generate representative simulated data so you can socialize a fully working system before connecting up your data sources. Swap simulated tags for real sources and the model is ready to operate.
  • Answers questions about live operations. Ask "How are my operations?" from inside tView or even from external clients like Claude (using the Transpara MCP server) and the AI calls Transpara's tools, reads live KPI data and the model (knowledge graph), ranks sites, identifies problems, traces root cause through the graph and/or calculations, and renders the answer in both text and visually. This is Seeking information - just one part of the AI story at Transpara.
  • Agents watching your operation continuously, even when you aren’t there. Specialist agents scan all of your KPIs and other metrics continuously, looking for things like outliers, KPIs approaching limits, drifting from baselines, regressing against prior periods, or going stale. This is also extensible, so you can add your own specific agents to the mix. When they find something significant, they post a briefing to the master agent, who determines what actually should be presented to users via chat, the activity feed, or via alerts. Imagine arriving in the morning and the system tells you what has happened since you last looked, what requires your attention, what problems are brewing, and what you might want to focus on. This is proactively Surfacing information.
  • Creating or adjusting calculations, the model/hierarchy, KPI limits, attributes and more. The same capabilities for end users are available to creators using tStudio, such as building or editing calculations using natural language, adjusting the model, and even monitoring the health of the system.

This is what "Industrial AI for Real-Time Operations" actually means in practice. Not a roadmap. Not a chat window. A system that watches, explains, predicts, prioritizes and suggests next steps, grounded in your live operational data and under your control at all times.

See AI Overview for the full picture.

What problems Transpara solves​

Most organizations struggle with operational data for the same three reasons.

The data is scattered. Sensors, historians, control systems, databases, cloud services, ERPs, and many other sources, all running at different speeds, frequencies, types (time-series, relational, documents, etc), locations (some on-premise, some cloud, some external) and none of them talking to each other.

The traditional fix takes years. Consolidate everything into a central data lake, build the "dream system" on top, and go live in twenty-four months. By the time you go live, the questions have changed, technology has moved on, and the company has reorganized twice. Most of these projects never finish.

Even when the data is combined, the tools are wrong for real-time decision making. Business intelligence is retrospective. Historians only account for part of your data. Dashboards show charts with no context and leave the interpretation to the user. The few tools that do offer AI usually bolt a chat window onto a dashboard and hope nobody asks a hard question.

Transpara takes a different approach. Connect to your existing systems in place. Standardize how the information is presented. Let AI watch the whole thing continuously. The Industrial Data Fabric (or Virtual Data Lake) makes data usable where it lives. The KPI model gives operators obvious status, color, and context. The graph database (tGraph) holds the relationships, model and hierarchy to keep things organized, and creates the unified namespace (it’s also what makes the AI features so powerful and future-proof).

The result is a single, live view of operations that scales across roles and sites, helping organizations act quickly, reduce risk, and improve performance without an infrastructure project that lasts longer than the questions it was trying to answer.

What Makes Transpara Unique​

The crowded analytics market is full of vendors making similar claims. A few things actually set Transpara apart.

KPI-focused, not dashboard-focused​

Most visualization tools start with a dashboard and ask the user to figure out what the numbers mean. Transpara starts with KPIs that have status, color, limits, and context built in. Add a few limits to a metric and it becomes a KPI that tells you "How is it going?" without anyone having to read a chart.

This sounds small. It changes everything. KPIs roll up cleanly through the hierarchy, so executives see the operation at a glance and engineers drill into the same data. AI agents can score KPIs against profiles and rank them automatically. Alerts come from the same definitions. Hundreds of visualizations generate themselves from consistent patterns. Operators don't need training to see whether something is wrong.

The Virtual Data Lake / Industrial Data Fabric​

The Virtual Data Lake (VDL) lets Transpara aggregate data from across your operations in real time, without forcing migration. Some sources Transpara reads in place, leaving the data where it lives. Others get persisted to tStore, Transpara's high-scale time-series database/historian, when retention or performance demand it. The choice is yours, source by source.

The effect is all the benefits of a data lake without the cost, time and risk of building one. You get a single pane of glass across historians, SCADA, OPC, MQTT, IoT, relational databases, cloud services, ERPs, and external sources, without copying data you don't need to copy or migrating data you don't need to migrate.

Rapid updates, deployed in days​

Time-to-value matters. Transpara deployments measure in days and weeks, not months and years. No-code configuration eliminates the need for large dev teams. Most customers operate Transpara globally with no full-time administrator. When something needs to change, it changes the same day.

The Model Builder takes this further. A model that would take weeks of manual configuration in a legacy tool can be optionally generated and adjusted in minutes using AI, refined in conversation, and pushed to a working environment. Customer pilots that used to take months can now be measured in days and weeks.

Graph-native AI​

AI that does meaningful root cause analysis needs to walk relationships at speed. Transpara's graph database (tGraph) makes this native. Tracing five levels of calculation dependencies to find the input that broke takes seconds.

Without a knowledge graph, "industrial AI" is reduced to a chat window with a search bar attached. One is just advanced search, the other is real agentic value creation and assistance.

Your data stays yours​

Transpara is not SaaS. The platform runs in your environment: on-premise, in your own cloud (public or private), or hybrid. The AI is optional and runs where you choose (public frontier models or locally running on-premise models). For high-security deployments, including nuclear, defense, and regulated utilities, fully air-gapped configurations are supported and in production today. Local models through Ollama and others mean the AI and your information never reaches the public internet.

When you do use a cloud model, the AI sees only what it needs to answer the current question, called through the structured MCP tools. It never gets raw database access or unrestricted credentials.

Built on operational memory​

Every alert, KPI change, comment, and finding becomes part of the system's operational memory. Comments capture what your team noticed and decided. AI findings record what the agents saw and what humans did about them. Over time, the graph becomes a record of how your operation actually runs, the kind of knowledge that used to live with the thirty-year veterans. This memory makes the next round of AI agents smarter.

Who Transpara is for​

Transpara is built for operationally intensive industries where real-time visibility and fast decisions matter.

Industries​

  • Mining and Metals. Surface and underground mining, mineral processing, asset-intensive operations, fleet coordination, water treatment.
  • Oil and Gas. Upstream, midstream, and downstream operations including refining, pipelines, terminals, and LNG.
  • Energy and Utilities. Electric and gas utilities, power generation (thermal, nuclear, hydro), grid operations, transmission and distribution.
  • Manufacturing. Discrete and process manufacturing, plant operations, OEE, and asset management.
  • Water and Wastewater. Municipal and industrial water systems, treatment plants, regulatory compliance.
  • Pulp and Paper. Paper mills and energy-intensive process environments.
  • Renewables. Wind, solar, geothermal, and hybrid generation with distributed assets.
  • Food and Beverage. High-throughput processing, compliance-heavy manufacturing, quality-focused plants.
  • Chemicals. Specialty, bulk, and commodity chemicals with safety, compliance, and uptime focus.
  • Telecommunications. Large-scale infrastructure operations, equipment uptime, data center operations, satellite.
  • Any industrial or real-time use case

A common pattern across all of them: distributed assets, moving data, mission-critical processes, expensive downtime, and information that is already flowing through existing systems.

Organizational profile​

Transpara fits best at larger enterprises with multi-site or geographically distributed operations. Most customers already have instrumentation, control systems, historians, time-series data, or IoT infrastructure in place. Transpara connects to what is already there.

Roles​

Each role gets something different from the same platform:

  • Executives and senior managers. Track performance across sites at a glance. Get briefings before the morning meeting. Align operations with strategic goals without waiting for someone to build a report.
  • Operations leaders and plant managers. See live asset health, production output, and resource usage. Intervene earlier. Allocate resources where they matter.
  • Engineers and reliability teams. Build the model, define KPIs, write calculations. Reusable templates eliminate duplicate work. AI helps with the heavy lifting.
  • Maintenance and field staff. Get the right information on any device, anywhere. Act on alerts. Collaborate through comments tied directly to the assets and KPIs that triggered them.
  • IT and administrators. Manage a system that runs in your environment under your control, integrates with Active Directory and SSO, and rarely needs hand-holding.

Transpara vs. Visual KPI​

If you are an existing Visual KPI customer, here is how the two products relate.

Visual KPI is the original lightweight, mobile-first visualization tool that put real-time KPIs in front of users without training. It is still supported, still deployed at hundreds of customers, and is not going away soon.

The Transpara Platform is the next-generation product. It follows the same core patterns as Visual KPI (KPIs, hierarchy, mobile-first, no-code) and amplifies them, while also adding the things Visual KPI does not have.

What's new in the Transpara Platform:

  • A graph-based asset model (tGraph). The foundation for industrial AI. Visual KPI used SQL Server.
  • A high-scale time-series database (tStore). Visual KPI relied on external historians for all time-series data.
  • An event-driven calculation engine (tCalc). Visual KPI did simpler on-the-fly calculations at runtime.
  • AI built in, not bolted on. The MCP Server, the Model Builder, and the autonomous monitoring agents are core platform capabilities.
  • The activity feed. A unified place to see AI findings, human comments, alerts, and mentions.
  • Modern web apps. tStudio replaces the Excel-based Visual KPI Designer. tView replaces the Visual KPI web client. Both are responsive, browser-only, and work on any device.

What stays the same:

  • The KPI focus that customers know Transpara for.
  • The principle of reading data in place where possible.
  • The no-code configuration philosophy.
  • The commitment to customer-controlled deployment.

There is no forced migration deadline. Visual KPI continues to be supported. Most customers move when a new capability in the Transpara Platform makes the move worth it, and the platforms can coexist while you transition.

For the mapping of specific Visual KPI components to their Transpara Platform equivalents, see the migration appendix in the FAQ.

What's next?​

Learn more about the system's Architecture or explore the Core Modules.