XPndAI builds bespoke robot fleet management cloud software for robotics manufacturers, system integrators, and enterprise operators deploying commercial and industrial robot fleets — warehouse AMRs, cleaning robots, inspection drones, factory cobots, logistics robots, service robots. Remote monitoring, predictive maintenance, after-sales service OS, digital twin, telemetry analytics, and multi-site fleet operations — in one cloud platform. Source code ownership. From $80,000. Built for Chinese robotics manufacturers expanding globally and enterprise operators deploying large-scale fleets.
The foundational layer of any robot fleet management platform is real-time visibility. XPndAI builds a multi-site fleet operations dashboard: live robot status (online / offline / charging / mission-active / error / maintenance) displayed on facility maps, real-time mission progress tracking (current task, estimated completion, mission queue depth), battery status fleet-wide (SoC%, estimated range, charging station availability, battery health trend), connectivity health (cellular/Wi-Fi/5G signal quality per robot), alert feed (error codes, obstacle encounters, mission failures, connectivity drops) with configurable severity levels, and performance metrics (tasks completed, distance travelled, uptime, utilisation rate per robot and per site). Multi-site view for enterprise operators managing robots across multiple warehouses, hospitals, airports, or factories — dashboard aggregates fleet health across all sites with drill-down to individual robot.
Reactive robot maintenance (repair after failure) causes unplanned downtime and expensive emergency service calls. XPndAI builds a predictive maintenance AI platform: continuous robot telemetry ingestion (motor current draw, joint torque signatures, vibration sensors, thermal profiles, wheel/track wear indicators, battery internal resistance, actuator response times, camera/sensor degradation metrics), AI anomaly detection (deviation from baseline signatures indicates developing fault — flagged before failure occurs), failure prediction (AI models trained on fleet-wide historical failure data predict which robots are likely to fail within N days, enabling scheduled maintenance before breakdown), maintenance scheduling integration (predicted maintenance tasks pushed to service calendar, parts pre-ordered), maintenance history (full service record per robot — parts replaced, issues found, technician notes), and component life tracking (track remaining useful life of wear parts — motor brushes, wheels, filters, batteries — and trigger replacement at optimal intervals).
For robotics manufacturers and distributors, after-sales service is a major revenue stream and customer satisfaction driver. XPndAI builds a complete robot after-sales service OS: service ticket management (customer reports issue → AI classifies severity → assigned to regional field service team with robot history pre-loaded), remote diagnostics (field engineer accesses robot telemetry, logs, and camera feed remotely before dispatching — resolves 30-40% of issues without site visit), spare parts management (parts inventory by region, automatic reorder at threshold, parts consumption tracking per robot model — identifies reliability issues), field service dispatch (optimised engineer scheduling based on geography, skill set, and robot model expertise), SLA tracking (response time and resolution time per contract type — warranty / extended warranty / time-and-materials / annual maintenance contract), customer portal (customer views their robot fleet status, open tickets, maintenance history, and invoices), and service revenue analytics (revenue by contract type, gross margin per service visit, engineer utilisation, parts profitability).
A digital twin creates a virtual replica of each physical robot, synchronised with real-time telemetry. XPndAI builds a robot digital twin platform: 3D robot model synchronised with live sensor data (joint positions, actuator states, sensor readings, battery state — visual representation of the physical robot's current state), environment mapping synchronisation (robot's SLAM map synchronised with digital twin — see where the robot is and what it sees), simulation environment (test software updates, new mission profiles, or configuration changes on the digital twin before deploying to physical robot — reduces risk of real-world disruption), remote operation interface (where the robot supports teleoperation — control the physical robot through the digital twin interface), failure scenario simulation (simulate fault conditions to test maintenance procedures and validate repair instructions before sending to field), and fleet-level digital twin (aggregate view of all robots in facility — optimise traffic flow, charging station placement, and mission allocation across the fleet).
Every robot generates continuous telemetry — sensor readings, actuator states, mission data, error logs, environmental observations. XPndAI builds the data infrastructure to collect, store, and analyse this data at scale: telemetry ingestion layer (protocol-agnostic: MQTT, ROS2/DDS, REST, WebSocket — connects to any robot platform), time-series data storage (optimised for high-frequency telemetry — 50+ sensors × thousands of robots × continuous stream), real-time analytics (live computation of KPIs — fleet utilisation, task completion rate, error frequency, battery efficiency), historical analysis (trend analysis over months/years — identify gradual performance degradation, seasonal patterns, long-term reliability trends), data API (analytics and telemetry accessible to customer's internal systems — ERP, WMS, CMMS integration), and multi-tenant architecture (for robotics manufacturers: each customer's fleet data isolated, manufacturer sees aggregate analytics across the entire deployed fleet — critical for R&D feedback).
Chinese robotics manufacturers entering the Indian market face unique localisation requirements. XPndAI builds an India Deployment OS for Chinese robots: language localisation (operator interface in Hindi/English/regional languages — operator staff on factory floor work in their language), local regulatory compliance support (BIS certification documentation, MSME scheme integration for buyer financing, Make in India compliance documentation, GST invoice generation for spare parts), local support network management (certified service partner network in India — onboarding, training materials, territory management, performance tracking), India-specific connectivity (cellular fallback for unreliable Wi-Fi in Indian industrial settings, local server deployment for data residency compliance), integration with Indian business systems (Tally Prime for service billing, IndiaMART/TradeIndia for parts sourcing, government GeM portal for institutional sales), and India-specific customer portal (WhatsApp-based service ticket submission — field staff use WhatsApp, not apps). Built to support Chinese robotics manufacturers' India market entry and Indian enterprises deploying Chinese-manufactured robots.
Autonomous Mobile Robots (AMR) and Automated Guided Vehicles (AGV) operating in warehouses, distribution centres, e-commerce fulfilment, and logistics facilities. Fleet management covers: mission queue management, pick-path optimisation, traffic management (collision avoidance scheduling, junction priority), charging station management (fleet-wide battery state optimisation, automatic charging dispatch), WMS integration (order data → mission generation), and utilisation analytics (picks per hour, km per shift, idle time reduction).
Autonomous floor scrubbers, sweepers, and sanitisation robots operating in airports, shopping malls, hospitals, hotels, and commercial facilities. Fleet management: cleaning schedule management, coverage mapping verification (did the robot clean the entire zone?), consumable tracking (water, cleaning solution, pad wear), hygiene compliance reporting (facility manager receives automated cleaning completion reports), and multi-floor operation management.
Collaborative robots (cobots) and industrial robots in manufacturing — automotive, electronics, food processing, pharmaceuticals. Fleet management: production schedule integration, process monitoring (cycle time, quality metrics, reject rate), preventive maintenance scheduling, safety incident tracking, OEE (Overall Equipment Effectiveness) analytics, and integration with MES (Manufacturing Execution System).
Autonomous inspection robots for infrastructure (oil & gas pipelines, power substations, data centres), and security patrol robots for commercial facilities. Fleet management: inspection mission scheduling, report generation (inspection images, anomaly flags, AI-assisted analysis), regulatory documentation (inspection records for compliance), patrol route management, incident logging, and integration with security management systems.
XPndAI's robot telemetry platform is designed to be protocol-agnostic, connecting to robots via the communication interface each robot supports. Supported protocols include: (1) MQTT — lightweight publish-subscribe protocol widely used for IoT and robot telemetry; XPndAI runs an MQTT broker (Mosquitto or AWS IoT Core) that receives robot telemetry streams; (2) ROS2/DDS (Robot Operating System 2 with DDS middleware) — for robots built on the ROS2 stack; XPndAI subscribes to ROS2 topics over DDS and bridges telemetry to the cloud platform; (3) REST API — for robots with cloud-native architectures that push telemetry via REST endpoints; (4) WebSocket — for real-time bidirectional communication, used for remote monitoring and teleoperation interfaces; (5) Proprietary SDK — for major commercial robot platforms (Boston Dynamics Spot, Fetch Robotics, Locus Robotics, Keenon, Pudu, BrainCorp, Gaussian, CloudMinds — where the manufacturer provides a software SDK), XPndAI integrates via the vendor SDK; (6) OPC-UA — for industrial robots and cobots (Universal Robots, KUKA, Fanuc, ABB — industrial automation standard). New protocol integrations are assessed during scoping. Integration typically requires 4–8 weeks depending on protocol complexity and robot manufacturer's documentation.
Yes — multi-manufacturer fleet management is one of the key value propositions for enterprise operators who have deployed robots from multiple vendors over time. XPndAI builds a unified fleet management layer above the manufacturer-specific SDKs and protocols, so an operator can monitor and manage AMRs from Vendor A, cleaning robots from Vendor B, and cobots from Vendor C in a single dashboard with consistent status representation, unified alerting, and consolidated analytics. Implementation approach: (1) Each robot type connects via its native protocol/SDK (as described in the protocol question); (2) XPndAI builds a normalisation layer that maps each vendor's telemetry schema to a unified internal data model (battery state, position, status, mission state expressed consistently regardless of vendor); (3) The unified dashboard and analytics operate on the normalised data; (4) Vendor-specific functions (proprietary mission programming, manufacturer-specific settings) remain accessible through vendor tools while the XPndAI platform handles the cross-fleet operations layer. This approach ensures you don't lose vendor-specific capabilities while gaining unified operational visibility.
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XPndAI · Robot Fleet Management Software · AMR / Cobot / Cleaning / Inspection Robots · Multi-Manufacturer · Source Code Ownership · From $80,000 · +91-9625368140 · 机器人车队管理软件