Industrial IoT
Predictive Maintenance Sensors and Edge AI for a Steel Plant
- Reduction in Unplanned Downtime
- 78%
- Client-reported
- Fault-Classification Accuracy
- 94%
- Measured in pilot
- Sensor Nodes Across 3 Plants
- 500+
Software and cloud
Secure device-cloud backends for connected products, including provisioning, identity, MQTT and API ingestion, digital twins, time-series data, OTA coordination, fleet monitoring and operational dashboards on AWS, Azure or Google Cloud.
Every project is quoted as a fixed-scope proposal within 3–5 business days of a discovery call. Discuss your product
Industrial IoT
Predictive Maintenance Sensors and Edge AI for a Steel Plant
Capabilities
Per-device X.509 certificates or secure-element credentials injected at manufacture, zero-touch registration and role-based access for operators and customers.
Telemetry ingestion through AWS IoT Core, Azure IoT Hub or a self-managed MQTT broker (EMQX, HiveMQ), with versioned message contracts and offline buffering.
Hot, warm and cold storage tiers on TimescaleDB, InfluxDB or Amazon Timestream for InfluxDB, with retention and downsampling agreed per data type.
Staged firmware campaigns by device cohort, signed images, progress reporting and rollback, coordinated with the firmware's A/B update scheme.
Fleet health, alerts and remote actions for operations teams, load-tested to the agreed device count.
Process
Agree device identity, message formats, timestamps, units and version compatibility across firmware and cloud teams.
Deliverable: Versioned device API and telemetry contracts
Choose a modular application or separate services according to deployment, ownership and scaling needs.
Deliverable: Architecture with monitoring, backup, access control and incident ownership planned
Exercise the complete device-to-dashboard workflow, including offline devices, permission failures and recovery.
Deliverable: Working application with access permissions tested for each user role
Hand over source and deployment access, configuration documentation, dependency licences and repeatable build instructions.
Deliverable: Release package; hosting, source ownership and support agreed
Planning
Start with a non-confidential summary of your product and the milestone you need to reach next.
An end-to-end cost breakdown for building an IoT product — hardware, firmware, connectivity, cloud and certification.
A vendor-selection framework with the evaluation criteria, questions to ask, and red flags to watch for when picking an engineering partner.
Proof
Industrial IoT
Steel manufacturer, India (3 plants)
Smart Agriculture
Agricultural cooperative, Maharashtra, India
Connected Fleet
Logistics and transportation company
Medical Wearable
US-based digital health startup
Digital Twin
Commercial real estate developer
Multi-Connectivity Pet Tracker
European pet technology company
Automated Nitric Oxide Therapy System
Medical equipment manufacturer, India
ToF Tank Level Monitor
Industrial client, India
Hotel Call-Button System
Hospitality client, Oman
FAQ
We have expertise across all major cloud platforms including AWS (IoT Core, Lambda, DynamoDB), Azure (IoT Hub, Functions, Cosmos DB), and Google Cloud (Pub/Sub, Cloud Run functions, Bigtable) with a self-managed MQTT broker, since Google Cloud IoT Core was retired in 2023. We can also implement hybrid or multi-cloud architectures based on your requirements.
Cloud cost optimization starts with intelligent data tiering, aggregating and downsampling high-frequency telemetry at the edge so only actionable data reaches expensive hot storage. Using reserved instances for predictable workloads, auto-scaling serverless functions for bursty event handling, and moving cold data to object storage reduce monthly cloud bills compared to always-on architectures; we model the cost at your fleet size before choosing.
We design cloud architectures using auto-scaling groups, serverless functions, message queues, and microservices patterns. Load balancing, caching strategies, and database optimization are designed to scale with fleet size, and the backend is load-tested to the agreed device count.
Our cloud security includes IAM policies with least-privilege access, VPC isolation, encryption at rest and in transit, secrets management, WAF configuration, DDoS protection, and comprehensive audit logging. We follow cloud provider security best practices and can support compliance requirements like SOC 2, HIPAA, and GDPR.
Yes, we specialize in integrating IoT platforms with existing enterprise systems including ERP (SAP, Oracle), CRM (Salesforce), SCADA/MES systems, and custom databases. We implement secure APIs, message brokers, and data transformation pipelines to ensure seamless data flow.
IoT cloud architectures typically follow an ingestion-processing-storage-presentation pipeline, with an MQTT or AMQP message broker at the edge, a stream processing layer for real-time analytics, and both hot and cold storage tiers for operational and historical data. Event-driven architectures using services like AWS IoT Core or Azure IoT Hub decouple device communication from backend processing, enabling independent scaling of each tier.
Time-series database selection depends on write throughput requirements, query patterns, retention policies, and cost at scale, with popular options including InfluxDB, TimescaleDB, and cloud-native services like Amazon Timestream for InfluxDB or Azure Data Explorer. For high-cardinality data from thousands of devices, purpose-built time-series databases significantly outperform general-purpose relational databases in both write performance and compressed storage efficiency.
Real-time IoT data streaming is typically implemented using lightweight publish-subscribe protocols like MQTT with QoS levels configured to balance reliability against bandwidth, feeding into cloud-side stream processing engines such as Apache Kafka, AWS Kinesis, or Azure Event Hubs. Edge gateways often buffer, aggregate, and compress telemetry locally before transmitting to reduce bandwidth costs and handle intermittent connectivity.
Multi-tenant IoT platform design must enforce strict data isolation between tenants at the device registry, message broker, database, and API layers, typically using tenant-scoped partitioning keys or separate database schemas. Noisy-neighbor mitigation through per-tenant rate limiting and resource quotas prevents one customer's traffic spike from degrading service quality for others.
Cloud-to-device command and control uses device shadow or digital twin patterns where the cloud writes a desired state to a shadow document, and the device synchronizes upon its next connection. For time-critical commands, direct method invocations via MQTT deliver instructions with acknowledgment responses within configurable timeout windows. Robust implementations include command queuing for offline devices and idempotent execution to handle retries safely.
IoT cloud platforms need configurable data retention policies that meet regulations such as GDPR, CCPA and, for healthcare, HIPAA; for industrial systems, IEC 62443 governs the security controls around that data. Automated data lifecycle management should enforce tiered retention with raw telemetry in hot storage, aggregated data in warm storage, and anonymized analytics in cold archive for long-term trend analysis.
Serverless functions like AWS Lambda are ideal for event-driven IoT workloads with variable traffic patterns because they scale to zero during idle periods and handle unpredictable bursts without capacity planning. Containerized microservices on Kubernetes are better suited for sustained high-throughput processing or stateful services. Many production IoT platforms use a hybrid approach with serverless for event ingestion and containers for stream processing.
Each project is quoted as a fixed-scope proposal: a statement of work with milestones, deliverables and pricing, sent within 3–5 business days of the discovery call. The price depends on the requirements, how mature the design is, technical complexity, the number of prototype iterations and the validation scope. Longer engagements can also run as a retainer or a hybrid of both. For budgeting before you contact us, our hardware development cost benchmarks and the PCB design, firmware and IoT cost guides give indicative ranges with their assumptions stated. They are planning ranges, not quotes.
It depends on the scope and on what already exists when we start. As planning ranges from our cost benchmarks: a single PCB layout takes 2–6 weeks per board and embedded firmware 4–16 weeks. A connected (IoT) product takes 3–12 months from concept to a production-ready design, and a regulated medical device 12–24 months to a 510(k) submission-ready package; from idea to mass production, a typical connected product takes 9–18 months. The proposal sets out a dated milestone plan, and you receive weekly progress updates during the project.
You do. Our contracts assign the intellectual property in the project work product (schematics, PCB design files, firmware source code and documentation) to you on payment, and we hand over the source files, not only fabrication outputs or compiled binaries. The exact terms are set out in the signed agreement for each engagement.
Yes. We sign a mutual NDA before any technical discussion of your project. Send your standard NDA or use ours; we return it signed within one business day.
Yes. We are based in Hyderabad, India, and work with product teams in India, the United States, the United Kingdom, Germany, Japan, Australia, the Middle East and other markets. Our office hours are 10:30–19:00 India Standard Time (UTC+5:30), Monday to Saturday, and we schedule design reviews across time zones, typically from US Pacific to Central European time. Japan is 3.5 hours ahead of India, so our first four hours overlap the Japanese afternoon. Prototypes and documentation ship by international courier such as DHL or FedEx. Our hardware outsourcing guide covers what to agree before an international project starts.
Yes. We prepare the manufacturing release package — fabrication and assembly drawings, the BOM with approved manufacturers, programming files and test specifications — and hand it over to the contract manufacturer (EMS) you choose. If you have not chosen one, we help you evaluate candidates through technical capability assessments and a pilot build. See manufacturing support.
No. Rapid Circuitry does not hold ISO 9001, ISO 13485 or other certificates. Our processes are aligned with ISO 9001:2015, and we design products to the requirements of the standards that apply to them — for example IEC 60601-1 and IEC 62304 for medical devices (with design documentation structured so your ISO 13485 quality system can absorb it) and IEC 61000 for EMC — and we specify IPC-A-610 workmanship classes for assembly. We prepare the product and its documentation for certification testing at accredited laboratories; the certificate or approval is issued for your product by the laboratory, notified body or regulator.
A short, non-confidential description of the product and what it must do (sensors, connectivity, on-device processing), the target production volume and unit cost, the markets and regulations it must meet (for example FDA, CE or FCC), your timeline, and what already exists: a concept, a proof of concept, schematics, PCB files or firmware. After the NDA, the next step is a 30-minute discovery call with the engineers who would work on the project, followed by the fixed-scope proposal. Send a project brief to begin.
Explore
Device APIs, provisioning, telemetry pipelines and companion-app backends for connected hardware.
iOS, Android and cross-platform companion apps: BLE or Wi-Fi onboarding, device control, alerts and OTA update flows.
Real-time IoT dashboards, fleet portals and customer web apps for connected products.