RaftLabs builds live operational dashboards that update automatically as underlying data changes. Fleet tracking maps, production line monitoring, financial market displays, and operations centre screens -- built for the contexts where decisions require current data rather than last-hour exports.
We design the full stack: the data pipeline from source to WebSocket or SSE delivery, the front-end chart and map rendering that updates without page flicker, and the alert and threshold management that tells your team when something needs attention.
Sub-second data updates via WebSocket or SSE -- no manual refresh required
Designed for high-frequency data without overloading the client browser
Alert and threshold management built in -- not bolted on after the fact
Multi-screen and operations centre layouts supported
RaftLabs builds real-time operational dashboards using WebSocket and Server-Sent Events. We deliver live fleet tracking maps, production monitoring screens, financial data displays, and IoT sensor dashboards with configurable alert management. A focused real-time dashboard -- single data source, defined chart set, alert thresholds -- runs $15,000-$50,000. A complex multi-source platform with geospatial mapping and multi-screen layouts runs $50,000-$120,000. Fixed cost, full data pipeline design included.
Trusted by
Operational decisions made on stale data are not really operational decisions -- they are historical analysis dressed up as real-time management. When your fleet tracking screen shows positions from three minutes ago, your dispatch team is not managing what is happening; they are managing what happened. When your production monitoring dashboard refreshes on a five-minute cycle, problems compound for five minutes before anyone sees them.
RaftLabs builds dashboards where the data on screen reflects reality within seconds of it changing. We design the full pipeline -- from data source through streaming infrastructure to front-end rendering -- and we solve the engineering problems that make high-frequency dashboards hard: throttling updates so the client is not overwhelmed, rendering efficiently so charts update without flicker, and managing alerts so your team is notified when thresholds are crossed rather than discovering issues during the next manual check.
Capabilities
What we build
Live operational monitoring dashboards
Custom operational dashboards that display current system state across whatever metrics your team monitors -- built for the update frequencies and data volumes your specific operation generates rather than adapted from a BI tool designed for hourly batch queries. WebSocket delivery for bidirectional control (operators can acknowledge alerts, trigger actions from the dashboard) and Server-Sent Events for unidirectional high-volume feeds where bidirectional overhead is unnecessary -- the choice made per data source based on interaction requirements. Server-side update batching and aggregation to prevent client overload: the server collects incoming events on a 250ms-1 second window, computes a diff against the last sent state, and pushes only the changed fields to connected clients -- a production monitoring board with 200 machines generates thousands of micro-events per second but the client receives a single compact update payload per batch interval. KPI tiles with configurable colour thresholds (green/amber/red status based on your defined ranges), animated counter transitions so changes are visually obvious without operators scanning every number, and a flashing state for values that have just changed within the last 5 seconds. Time-series charts using uPlot for high-frequency data: uPlot renders 1 million data points in under 40ms using WebGL, making it viable for dense rolling windows that Recharts and Chart.js cannot handle at smooth frame rates. Status grids for monitoring large numbers of assets or services: each cell shows the current status colour, last update time, and the most recent metric value -- the layout that works on operations centre walls where dozens of assets need a simultaneous view. Drill-down on any tile or chart cell to an expanded detail view showing the full historical window, related metrics, and the alert history for that asset or data point.
Fleet and asset tracking maps
Geospatial dashboards that show asset positions, routes, and status updating as location events arrive -- built for the specific performance requirements of large fleets where rendering hundreds of simultaneously moving markers at smooth frame rates requires different architecture than a static map with occasional updates. WebSocket-delivered location events from your GPS tracking provider or IoT platform, normalised to a consistent event schema and fanned out to connected dashboard clients via a Redis Pub/Sub broadcast -- so 500 connected operators watching the same fleet each receive every location update without the server processing 500 separate queries per event. Mapbox GL JS for smooth vector tile maps with custom asset marker layers: each asset rendered as a custom symbol layer with real-time position interpolation so movement appears smooth rather than teleporting between GPS fixes. Deck.gl for very large fleets (thousands of simultaneously visible assets): Deck.gl's WebGL-based rendering handles 50,000 animated markers at 60fps where CSS/SVG-based approaches collapse at 200. Cluster handling using supercluster for dense areas: assets within proximity grouped into count clusters at lower zoom levels and exploded to individual markers at higher zoom. Geofence alert overlays: configured polygon geofences rendered as translucent map layers, with server-side entry/exit event detection generating alerts when an asset crosses a boundary -- alert fires within 1 GPS update cycle (typically 10-30 seconds) of the crossing. Route history as a toggle layer: the last N hours of breadcrumb trail for selected assets rendered as a line layer, useful for post-event investigation without leaving the live view. Multi-fleet views with fleet-level filtering: operations teams managing multiple customer fleets see all assets simultaneously and can filter to a single fleet by clicking a fleet selector without a page navigation.
Financial and trading data displays
High-frequency price, volume, and position displays for financial and trading applications -- built around the update frequencies and rendering requirements that financial data sources produce, which are fundamentally different from operational dashboards designed for 1-second update cycles. TradingView Lightweight Charts for OHLCV (open/high/low/close/volume) candlestick and bar charts: the library is purpose-built for financial time series, renders on canvas rather than SVG, and handles streaming tick data appended to the rightmost bar without re-rendering the entire chart history. uPlot for multi-series price and volume panels where multiple instruments are displayed simultaneously: sub-millisecond render time per frame maintains smooth updates at the 100+ events-per-second rates that equity and crypto data feeds produce. Order book depth visualisation using a WebSocket feed from your exchange or market data provider: bid and ask ladders rendered as a stacked bar chart with colour-coded sides, updating at the raw feed rate for the most actively traded instruments. WebSocket feed management for multiple simultaneous data source subscriptions: subscription multiplexing over a single connection to avoid the connection limit issues that arise when each chart subscribes independently to the data feed. P&L tracking with real-time mark-to-market: position inventory crossed with live price feed to compute unrealised P&L per position and total portfolio P&L updating on every price tick. Risk threshold alerts: configurable per-position and portfolio-level exposure limits that trigger visual and audio alerts when breached, with the alert data logged to a database for compliance and audit purposes. Data normalisation layer for heterogeneous feed formats: different market data providers use different message schemas, and we build the normalisation layer that maps each provider's format to your application's canonical price/volume schema.
IoT sensor data dashboards
Live sensor readings from temperature, pressure, vibration, flow rate, current, and humidity sensors delivered to dashboard displays as they arrive from your IoT data pipeline -- built for the data volumes and device counts that industrial and facility monitoring deployments generate, where thousands of sensors report at sub-minute intervals and the combined event stream requires server-side aggregation before it reaches any dashboard client. MQTT-to-WebSocket bridge for devices that publish on MQTT (the standard protocol for IoT sensors): a bridge service subscribes to your MQTT broker (AWS IoT Core, Mosquitto, HiveMQ), processes incoming sensor payloads, applies per-sensor calibration corrections and engineering unit conversions (raw ADC value to Celsius, raw counts to RPM), and broadcasts normalised readings to WebSocket subscribers. Gauge and meter displays for scalar readings: configurable min/max range, colour zone bands (green/amber/red) aligned to your defined operating limits, and a numeric readout with units -- the display format that gives operators the fastest possible out-of-range identification. Rolling trend charts for sensor history: the last 30 minutes to 24 hours of readings shown as a continuous line chart with the current value annotated, zoom and pan for investigating anomalies in historical context without leaving the live view. Vibration spectrum analysis display for machinery monitoring: FFT frequency domain charts generated server-side from raw accelerometer data, updated at a configurable cycle (typically 10-60 seconds) and displayed alongside time-domain amplitude for identifying bearing defects and imbalance signatures. Alert thresholds configured per sensor with hysteresis to prevent alert flapping: a temperature sensor set to alert above 85°C will not re-alert immediately if the value drops to 84°C and rises again -- the hysteresis band (configurable, typically 2-5% of the threshold value) prevents nuisance alerts from noisy sensors near threshold values.
Alert and threshold management
Configurable alert rules evaluated server-side so notifications fire within seconds of a threshold being crossed rather than on the next dashboard poll cycle -- the distinction that matters when a five-minute poll cycle means a process failure compounds for five minutes before anyone knows. Alert rule engine supporting simple threshold rules (temperature above 85°C), rate-of-change rules (pressure increasing faster than 5 PSI/minute), absence rules (no heartbeat from sensor within 60 seconds), and composite rules combining multiple conditions with AND/OR logic (temperature above 80°C AND pressure above 150 PSI). In-dashboard alert banners appearing at the top of the dashboard with the asset name, the breached threshold, the current value, and the time the alert fired -- visible to all connected operators simultaneously via the same WebSocket channel that delivers live data, so no operator is watching a stale view while others see an active alert. Sound alerts for critical severity events: configurable audio notification with distinct tones for different severity levels so operators monitoring multiple screens can react to a critical alert without looking up. Acknowledgement workflow: an operator claims an alert by clicking Acknowledge, which records the claiming user's identity and timestamp, changes the alert status to "acknowledged", and removes the alert from the queue of other operators watching the same asset -- preventing multiple operators from independently responding to the same event. Escalation chain for unacknowledged alerts: a critical alert unacknowledged for a configurable period (typically 5-15 minutes) escalates automatically to email, SMS via Twilio, or PagerDuty -- configurable per alert severity and per asset group. Alert history log with full detail: every alert fired, acknowledged, and resolved with the operator who responded, the resolution time, and the sensor values surrounding the event -- exportable for RCA (root cause analysis) and compliance reporting.
Multi-screen operations centre displays
Dashboard layouts designed for operations centre walls, multi-monitor workstations, and unmanned display screens that run continuously without operator interaction -- with the specific design decisions that make large-format and unattended displays effective rather than just scaled-up versions of desktop dashboards. Full-screen layout mode removes all browser chrome and navigation, leaving only the dashboard panels. Grid-based layout builder: the dashboard canvas divided into configurable rows and columns with panels snapping to grid cells, resizable by drag, and saved as named layout presets that operators switch between with a keyboard shortcut. TV and large-format display optimisation: font sizes, chart line weights, and tile padding tuned for viewing at 3-8 metres rather than 60cm -- the standard desktop dashboard is unreadable at operations centre wall distances. Auto-rotating presentation mode cycles through multiple saved dashboard layouts on a configurable timer (e.g., production line A for 30 seconds, production line B for 30 seconds, alert summary for 15 seconds) without any operator interaction -- the standard mode for unmanned display screens in control rooms. Role-based display profiles control which panels are visible and which are editable per user role: a supervisor sees financial targets and cross-line comparisons, an operator sees their individual line's metrics and current alert queue, a senior manager sees the summary KPI board -- each profile loading automatically based on the authenticated user's role assignment. Kiosk mode for shared workstations: the dashboard locks to a specific role profile without exposing browser navigation, appropriate for purpose-built display hardware in factory or warehouse environments where the screen serves a single function.
Your team is making decisions on data that is already old.
Tell us what your current refresh cycle is and what data source you are pulling from. We will tell you what a real-time layer would cost and how long it would take to deliver.
Event-Driven Architecture -- event streaming infrastructure that feeds real-time dashboards at scale
Related services
IoT Development -- IoT data pipelines and sensor infrastructure that feed real-time dashboards
Predictive Analytics -- predictive model outputs surfaced on real-time operational dashboards
Frequently asked questions
A BI dashboard is built for analysis -- it queries a data warehouse, runs aggregations, and renders charts that help you understand what happened over a time period. A real-time dashboard is built for operations -- it shows you what is happening right now so you can act on it. The data pipeline is different (streaming vs batch), the update mechanism is different (WebSocket/SSE vs scheduled query), and the front-end rendering requirements are different (incremental update without page reload vs full chart re-render on demand). Many businesses need both: a real-time operations view and a BI view for trend analysis. We build the real-time layer and can advise on how to integrate it with your existing BI tooling.
Client-side rendering has a practical ceiling -- if your data source emits 1,000 updates per second, pushing every one to the browser will consume all available CPU and produce a display that changes faster than any human can read. We solve this with server-side throttling and aggregation: the server batches updates at a configurable interval (typically 250ms to 1 second depending on the use case), aggregates them into a single diff, and sends the smallest payload that accurately represents the current state. Charts and maps receive only the data they need to update their current view, not a full re-render payload on every event.
We select charting libraries based on your specific requirements. For high-frequency time-series data, lightweight canvas-based libraries like uPlot or TradingView Lightweight Charts handle rapid updates without DOM overhead. For complex multi-chart operational dashboards, Recharts and ECharts provide the flexibility and customisation your design requires. For maps and geospatial dashboards, Mapbox GL and Deck.gl handle large numbers of moving assets at smooth frame rates. We recommend the right tool for your data volume and visual complexity rather than defaulting to a single library for everything.
A focused real-time dashboard -- single data source, a defined set of charts and metrics, alert thresholds, and basic user configuration -- typically runs $15,000 to $50,000. A complex multi-source platform with geospatial mapping, multi-screen layout support, role-based views, historical overlay, and advanced alert management ranges from $50,000 to $120,000. We scope each engagement with a clear definition of data sources, update frequency, and chart inventory before providing a fixed-cost quote.
Work with us
Tell us what you need. We'll tell you what it would take.
We scope Real-Time Dashboard Development in 30 minutes. You walk away with a clear cost, timeline, and approach. No commitment required.
Scope and cost agreed before work starts. No surprises. No obligation.
Working prototype within 3 weeks of kickoff.
Pay by milestone. You see progress before each invoice.
60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.