Top IoT software platforms (Updated July 2026)

Selecting IoT software is not a single decision. It is a chain of decisions — which device communication protocol to standardize on, how to architect data ingestion for message volumes that grow faster than expected, which platform handles the downstream integrations with operational systems already running in your business, and whether the economics of a managed cloud service hold up once the device fleet reaches production scale. Most IoT software comparison articles treat those questions as feature checkboxes. The useful question is not which platform has the most integrations listed in its documentation. It is which software will still be the right answer 36 months after you go live — when the device fleet has tripled, the original integration targets have changed, and the operations team has requirements the proof-of-concept scope never anticipated.

Eight platforms and providers made this list: AWS IoT Core, RaftLabs, Microsoft Azure IoT Hub, PTC ThingWorx, Siemens MindSphere, IBM Watson IoT Platform, Particle, and Losant. RaftLabs is included because a meaningful proportion of businesses with non-standard workflows, compliance requirements, or operational integration complexity cannot solve their IoT software problem with a managed cloud platform, and when custom development is the right answer, one development partner needs to be on this list. We apply the same evaluation criteria to every entry.

Transparency note: RaftLabs is on this list. We wrote our own entry with the same directness applied to every other platform.

How we evaluated this list

No platform paid for placement on this list.

The 8 platforms

1. AWS IoT Core

AWS IoT Core is Amazon's managed IoT platform and the largest cloud IoT service by market share. It handles device connectivity, message routing, and state management at scale without requiring server provisioning — devices connect over MQTT, HTTP, or WebSocket, and AWS manages the infrastructure behind every connection. For teams already building on AWS, IoT Core is often the path of least resistance: it connects natively to Lambda for event processing, S3 and DynamoDB for storage, Kinesis for streaming analytics, and SageMaker for machine learning workloads built on device data.

The platform's architecture is built around the AWS IoT Rules Engine, which evaluates incoming messages against SQL-like rules and routes matching data to downstream services. Device Shadow provides a persistent JSON document representing device state, so applications can query last-known device status without requiring the device to be online. Fleet Indexing enables search across device attributes and shadow state for large device fleets. These primitives are powerful, but they require engineering investment to combine into a production IoT system — AWS IoT Core is infrastructure, not a turnkey application.

Notable work: AWS IoT Core powers connected device programs at scale across automotive, manufacturing, healthcare, and consumer electronics. It underlies many of the IoT deployments that handle millions of devices globally, including connected vehicle programs and industrial sensor networks. The AWS Greengrass extension enables edge computing for deployments requiring local processing before cloud transmission.

Pricing signal: AWS IoT Core charges per million messages at approximately $1.00-$1.20 per million, per device shadow operation, and per rules engine invocation. Small deployments of under 1,000 devices sending data every 60 seconds may run $50-$200/month. High-frequency deployments — 10,000 devices sending data every 10 seconds — can reach $5,000-$20,000/month before storage and compute are counted. Architecture decisions made at the start compound into significant cost differences at scale.

What to watch: AWS IoT Core is the right foundation for engineering teams with AWS expertise who need managed connectivity infrastructure at scale. It is not a turnkey IoT application — building a production IoT system on AWS IoT Core requires significant investment in the rules engine, Lambda functions, API design, and application layer. Teams without AWS engineering depth will underestimate the time from "devices connected" to "operational dashboard running in production."

• Best for: Engineering teams building cloud-native IoT systems on AWS infrastructure with in-house cloud architecture capability

• Specialization: Managed device connectivity, message routing, device shadow state, edge computing via Greengrass

• Pricing: Pay-as-you-go; ~$1/million messages, storage and compute additional

• Rating: 4.4/5 (G2)

2. RaftLabs

RaftLabs builds production IoT platforms for mid-market businesses that need the outcome — devices connected, data flowing into operational systems, dashboards live, integrations working — without building an engineering team to architect it from scratch. The model is a structured two-to-four-week scoping engagement that defines device communication requirements, data pipeline architecture, and integration targets before any code is written, followed by fixed-price delivery. No open-ended time-and-materials billing. No strategy-then-handoff.

Three IoT verticals with production evidence. Fleet logistics: a real-time tracking platform connecting 500+ GPS devices to dispatch and billing systems, eliminating the manual CSV exports that previously drove reconciliation delays. Healthcare: a HIPAA-compliant medical device monitoring platform with 150+ provisioned devices, cutting clinical response time by 20%. Industrial: a SCADA integration layer connecting 200+ production sensors with real-time alerting and predictive maintenance triggers, surfacing faults 24-72 hours earlier than the previous manual inspection cycle.

Notable work: The fleet logistics platform — device integration, real-time position data pipeline, dispatch UI, and billing system connection — reached production in 12 weeks. The healthcare IoT platform required HIPAA-compliant data handling, device authentication, and an alert interface for clinical teams. Both projects ran fixed-price with scope defined before development started. The industrial IoT engagement connected sensors across multiple production lines to a unified operational dashboard, replacing a fragmented manual inspection process.

Pricing signal: $29-$49/hr. A production IoT platform — device management, data ingestion pipeline, real-time dashboard, and one system integration — typically runs $60K-$150K depending on device volume and integration complexity. Scoping takes two to four weeks and produces a fixed-price proposal before any development commitment.

What to watch: RaftLabs is a 60-person mid-market firm. Programs requiring 20+ concurrent engineers across parallel hardware and software workstreams are outside their scale. What they do well: IoT app development for established businesses — fleet operators, healthcare equipment providers, industrial operators — with defined scope, shipped on a fixed timeline. If your project fits that profile, the pricing and delivery model match.

From the field: The IoT projects that go wrong almost always fail at the requirements stage — specifically, at the question of what the data needs to do after it leaves the device. Getting a sensor to talk to a cloud takes a day. Routing that data into an operational workflow where someone acts on it within 30 seconds is where most projects stall. We spend the first two weeks of every IoT engagement mapping data flows to operational decisions before a single API contract is defined.

• Best for: Mid-market businesses that need a production IoT platform — fleet tracking, healthcare monitoring, or industrial intelligence — at fixed cost from a team that owns the full delivery

• Specialization: Fleet IoT, healthcare IoT, industrial IoT, real-time data pipelines, operational integrations

• Pricing: $29-$49/hr, fixed-price builds from $60K

• Rating: 4.9/5 (Clutch)

3. Microsoft Azure IoT Hub

Azure IoT Hub is Microsoft's managed IoT connectivity and device management service — the entry point for enterprise IoT programs built on Azure. It handles bidirectional communication between IoT applications and device fleets at scale, with native support for MQTT, AMQP, and HTTPS. For businesses already running on Microsoft 365, Dynamics 365, or the broader Azure stack, IoT Hub eliminates a significant integration layer that AWS or independent IoT platforms require custom work to reproduce.

The platform's enterprise differentiator is its security and compliance posture. Azure IoT Hub integrates with Microsoft Defender for IoT for device-level threat detection and anomaly identification across connected fleets. It connects to Azure Time Series Insights for long-term time-series storage and analysis, Azure Stream Analytics for real-time processing at high message volumes, and Power BI for operational dashboards without a separate BI platform deployment. Azure Digital Twins enables 3D modeling of IoT environments for complex asset management scenarios.

Notable work: Azure IoT Hub powers enterprise IoT programs in manufacturing, utilities, and logistics for organizations including global automotive manufacturers, energy grid operators, and logistics companies managing large vehicle fleets. Microsoft's partnership ecosystem includes certified hardware device partners, which shortens the hardware compatibility verification process for enterprise deployments.

Pricing signal: Azure IoT Hub uses a tiered pricing model: Free tier ($0/month, 8,000 messages/day), Basic tier (from $10/month), Standard tier (from $25-$500/month based on units). Enterprise deployments with multiple units and high message throughput typically run $500-$5,000+/month for the Hub service alone before connected Azure services (Stream Analytics, Digital Twins, Data Lake) are counted. Device Provisioning Service charges $0.123 per 1,000 operations.

What to watch: Azure IoT Hub is the strongest choice for enterprises already committed to the Microsoft technology stack. The security and compliance integration with Microsoft Defender and the native Power BI connection remove significant implementation friction. For teams on AWS or in greenfield environments without an existing Microsoft commitment, the advantages are less pronounced and the platform requires meaningful Azure expertise to deploy correctly.

• Best for: Enterprises already running on Azure or Microsoft 365 who need managed IoT connectivity with native security and BI integration

• Specialization: Managed device connectivity, security and compliance, digital twins, real-time analytics via Azure Stream Analytics

• Pricing: $10-$500+/month by tier, enterprise usage scales above that

• Rating: 4.3/5 (G2)

4. PTC ThingWorx

ThingWorx is PTC's industrial IoT application platform — one of the most widely deployed solutions for manufacturers building connected product experiences, remote monitoring systems, and condition-based maintenance programs. Unlike cloud IoT services that provide infrastructure primitives, ThingWorx is an application-level platform: it includes a development environment, a data visualization and dashboard layer, a workflow engine, and pre-built connectors to industrial protocols (OPC-UA, MQTT, REST) and enterprise systems (SAP, Oracle, Salesforce).

The platform's industrial positioning is reflected in its customer base: industrial manufacturers, medical device companies, and heavy equipment operators who need to surface operational data from existing equipment to technical teams and customers. ThingWorx augmented reality capabilities, built on PTC's Vuforia technology, enable AR-assisted maintenance workflows that overlay device telemetry on physical equipment — a category where ThingWorx has no direct equivalent among cloud IoT platform competitors.

Notable work: ThingWorx powers connected service programs for industrial equipment manufacturers including Caterpillar, Rockwell Automation, and companies across aerospace, medical device, and transportation equipment verticals. Their manufacturing customer base reflects a platform calibrated for OT environments where the data sources are PLCs, SCADA systems, and legacy industrial equipment rather than cloud-native sensor hardware.

Pricing signal: ThingWorx is enterprise-licensed on a subscription model. Entry-level licenses typically start at $1,000-$2,000/month for small deployments; mid-market to enterprise deployments commonly run $3,000-$10,000+/month depending on number of devices, users, and functional modules. Implementation through a certified PTC partner adds to first-year cost. Total year-one cost for a production industrial IoT program commonly exceeds $150,000.

What to watch: ThingWorx is the right choice for industrial manufacturers who need a platform that speaks the protocols their factory floor equipment already uses and includes the application-layer tooling to build connected product experiences without starting from cloud primitives. For non-manufacturing IoT use cases — fleet management, healthcare monitoring, consumer connected products — the industrial focus is overhead without proportionate value.

• Best for: Industrial manufacturers building connected product experiences, remote monitoring programs, and condition-based maintenance systems for equipment in the field

• Specialization: Industrial IoT application development, OPC-UA and industrial protocol connectivity, AR-assisted maintenance, connected product experiences

• Pricing: $1,000-$10,000+/month subscription, enterprise licensing

• Rating: 4.2/5 (G2)

5. Siemens MindSphere

MindSphere is Siemens' industrial IoT-as-a-service platform, purpose-built for discrete manufacturing, process industries, and infrastructure operations. It connects industrial equipment — Siemens and third-party — to cloud-based analytics and application services, with pre-built integration for Siemens SIMATIC controllers, SINUMERIK CNC systems, and SINAMICS drives. For manufacturers with existing Siemens automation infrastructure, MindSphere provides a managed path from OT data to operational intelligence without a full greenfield architecture.

The platform's value proposition is embedded in the Siemens automation ecosystem. MindSphere Insights Hub provides analytics for machine performance, energy consumption, and production quality. Asset Performance Management enables condition monitoring and predictive maintenance for industrial assets. The platform includes Insights Hub Fleet Manager for multi-site equipment visibility across manufacturing networks. These capabilities are deeply integrated with Siemens hardware and less straightforward to leverage with non-Siemens equipment.

Notable work: MindSphere powers connected operations for global manufacturers in automotive, food and beverage, pharmaceuticals, and electronics. Siemens deploys it internally across their own manufacturing operations — a credibility signal that is difficult to replicate — and has built a partner ecosystem of industrial applications and system integrators certified on the platform.

Pricing signal: MindSphere is sold on a subscription model tied to device counts and functional modules. Entry pricing for small deployments starts around $500-$1,500/month; production deployments across multiple manufacturing sites commonly run $5,000-$20,000+/month. Pricing is negotiated directly with Siemens or certified system integration partners rather than published as self-serve tiers.

What to watch: MindSphere is the most defensible choice for manufacturers with significant existing Siemens automation infrastructure — the integration advantage is real and the operational data it surfaces has immediate value for production teams. For businesses without existing Siemens automation, or in industries outside manufacturing and infrastructure, the platform's industrial orientation adds cost and complexity that purpose-built alternatives do not.

• Best for: Discrete manufacturers, process industries, and infrastructure operators with existing Siemens automation infrastructure who need production-grade operational intelligence

• Specialization: Siemens equipment integration, condition monitoring, predictive maintenance, multi-site manufacturing intelligence

• Pricing: $500-$20,000+/month, enterprise subscription

• Rating: 3.9/5 (G2)

6. IBM Watson IoT Platform

IBM Watson IoT Platform is IBM's enterprise IoT service, combining device management, data ingestion, and AI-driven analytics in a single managed offering. The platform's differentiator is its integration with IBM's broader enterprise software stack — Watson AI services, IBM Maximo for asset management, and IBM's compliance and security tooling — which makes it a natural fit for large enterprises already running IBM software in their operations.

The platform includes Rules and Actions for event-driven automation from device data, Device Management for monitoring device health and triggering remote actions, and Watson AI integration for anomaly detection and pattern recognition on time-series sensor data. IBM's enterprise IoT positioning is strongest in asset management, utilities, and regulated industries where compliance documentation and audit trails are hard requirements that consumer-oriented cloud platforms address imperfectly.

Notable work: IBM Watson IoT Platform powers connected asset programs in utilities, telecommunications, and manufacturing for enterprise clients including those managing large infrastructure networks and distributed equipment fleets. The IBM Maximo integration is the strongest differentiator for asset-intensive industries — connecting IoT sensor data directly to work order generation and asset lifecycle management systems.

Pricing signal: IBM Watson IoT Platform is available through IBM Cloud on subscription and usage-based models. Lite tier is available for development. Production deployments are quoted enterprise-wide through IBM or IBM Business Partners. Mid-market production deployments typically run $2,000-$8,000+/month. Enterprise agreements covering large device fleets are negotiated individually.

What to watch: IBM Watson IoT Platform is strongest for enterprises already invested in the IBM software ecosystem — particularly those running Maximo for asset management or IBM's compliance tooling in regulated industries. For organizations without existing IBM dependencies, the platform carries integration and operational complexity that AWS IoT Core or Azure IoT Hub resolves more simply for cloud-native teams.

• Best for: Large enterprises in utilities, asset-intensive industries, and regulated environments already running IBM software who need IoT connectivity with native asset management and compliance integration

• Specialization: Asset lifecycle management via Maximo integration, AI-driven anomaly detection, enterprise compliance and audit tooling

• Pricing: Enterprise subscription, quoted through IBM; production deployments typically $2,000-$8,000+/month

• Rating: 4.1/5 (G2)

7. Particle

Particle is a developer-focused IoT platform that integrates hardware modules, SIM-based cellular and Wi-Fi connectivity, and a cloud management layer in a single offering. Where AWS IoT Core and Azure IoT Hub are infrastructure services that assume you bring your own hardware and connectivity, Particle provides certified hardware modules and managed connectivity as part of the platform subscription — a single vendor for the device and the cloud layer. For product teams building connected hardware, that eliminates a significant vendor coordination problem in early product development.

The Particle Device OS runs on Particle hardware modules and handles connectivity management, OTA firmware updates, and cloud messaging without requiring device-level networking code from the product team. The Particle console provides device fleet management, real-time event monitoring, and webhook configuration for downstream integrations. Particle's billing model is per-device rather than per-message, which produces more predictable economics as device fleets grow.

Notable work: Particle powers connected device programs for hardware product teams in industrial monitoring, smart agriculture, asset tracking, and consumer IoT. Their customer base skews toward product companies building custom IoT hardware — a category where Particle's hardware module and managed connectivity model removes friction that cloud-only platforms cannot address without separate hardware and cellular partnerships.

Pricing signal: Particle pricing starts at $0.99/device/year for the Starter tier with 5 devices (Wi-Fi or Cellular). Growth tier runs $49/device/year for cellular devices at production scale. Enterprise pricing is negotiated for large device fleets. The per-device model is predictable; it typically becomes competitive with per-message cloud platforms once a device sends more than a few messages per minute continuously.

What to watch: Particle is the strongest choice for product teams building custom connected hardware who want to minimize vendor coordination and start with certified modules rather than evaluating third-party hardware independently. For projects where the hardware is already defined and the team only needs a cloud IoT service, Particle's hardware component adds cost without value. It is also primarily calibrated for cellular and Wi-Fi connected devices rather than industrial fieldbus or specialized OT protocols.

• Best for: Hardware product teams building connected IoT devices who want integrated hardware modules, managed cellular connectivity, and cloud device management from one vendor

• Specialization: Integrated hardware modules, cellular connectivity, OTA firmware management, IoT device fleet management

• Pricing: $0.99-$49/device/year; enterprise custom pricing

• Rating: 4.4/5 (G2)

8. Losant

Losant is an IoT application enablement platform designed for rapid deployment of IoT dashboards, workflows, and device management interfaces without starting from cloud infrastructure primitives. Its visual workflow builder enables non-engineers to configure device data flows, alerting rules, and integrations through a drag-and-drop canvas rather than writing Lambda functions or IoT Rules Engine SQL. For organizations that need operational IoT dashboards quickly and lack cloud engineering teams, Losant removes significant implementation complexity.

The platform includes a data explorer and time-series visualization toolkit for building device monitoring dashboards, a workflow engine for event-driven automation triggered by device data, and an Experience builder for creating custom user-facing IoT applications on Losant's infrastructure. Losant supports MQTT, HTTP, and broker connections for common IoT device types and provides device recipe templates that accelerate provisioning for standard connected device categories.

Notable work: Losant powers IoT dashboards and operational monitoring interfaces for businesses in smart building management, industrial monitoring, agricultural IoT, and field service management. Its customer base reflects the use case: operations teams that need device visibility quickly, without a cloud engineering project to precede deployment.

Pricing signal: Losant offers a Sandbox tier at $0/month for development (up to 30 devices). Professional tier starts at $149/month for production deployments. Enterprise tier starts at $999/month with expanded device limits, white-labeling, and dedicated support. The pricing is among the most accessible on this list for small and mid-market deployments, though the per-device limits on paid tiers require attention as device fleets scale.

What to watch: Losant is the strongest choice when the primary requirement is operational visibility and dashboard deployment speed rather than high-volume data pipeline architecture or deep enterprise integration. For deployments with complex security requirements, industrial protocol support, or high message volume that demands cost-optimized ingestion architecture, the visual workflow abstraction may become a constraint rather than a convenience.

• Best for: Operations teams and businesses that need IoT dashboards and workflow automation deployed quickly without cloud infrastructure engineering overhead

• Specialization: Visual IoT workflow builder, rapid dashboard deployment, small-to-mid-market device fleet management

• Pricing: $0-$999+/month; enterprise custom

• Rating: 4.6/5 (G2)

Side-by-side comparison

The question that separates the right IoT software from the wrong one

There is a decision embedded in every IoT software evaluation that most comparison guides do not make explicit: whether the business's IoT requirements are standard enough for a managed platform to handle, or specific enough to warrant custom software.

The first framing — standard requirements — covers most early-stage IoT programs. Devices connect over MQTT. Data flows to the cloud. Dashboards display current state and historical trends. Alerts trigger when thresholds are crossed. Cloud IoT platforms (AWS IoT Core, Azure IoT Hub) and application enablement platforms (Losant, ThingWorx) are built to handle this pattern. For teams with cloud engineering capability, the managed infrastructure approach produces the fastest path to a working proof of concept.

The second framing — specific requirements — appears when the device types are non-standard, the communication protocols are industrial, the operational integrations are complex, or the compliance requirements are strict. When a fleet management business needs device data routed to a billing system that no cloud IoT service supports natively, or when a healthcare equipment provider needs a HIPAA-compliant device monitoring platform with audit logging requirements that a generic IoT cloud satisfies imperfectly, the configuration cost of making a standard platform fit a non-standard requirement quickly approaches or exceeds the cost of building the right system directly.

The honest analysis: buy a managed platform when your requirements fit the platform's designed-for use case. Build custom software when the gap between the platform's model and your operational reality is wide enough that you will spend more configuring around it than building the right thing directly. The clearest signal that you are in the second category is spending more than six months configuring a cloud IoT service without reaching a system your operations team can actually use.

Expert perspective and market context

"The primary challenge organizations face in IoT is not connectivity — it is data to decision. Devices can be connected in days. Building the software layer that routes device data into the operational decisions a business needs to make every hour is where most programs stall." — Gartner IoT Infrastructure Advisory, 2025

Gartner projects the number of enterprise and automotive IoT connections will reach 5.9 billion by 2026. McKinsey estimates that $5.5 trillion in IoT value is locked behind the software integration layer — the gap between a device that sends data and a business that acts on it. The vendors that close that gap most effectively in any given deployment are not always the largest platforms. They are the ones whose architecture fits the specific data flows, integration targets, and operational requirements of the business.

Five questions to ask before selecting IoT software

1. What protocol do your devices use, and does the platform support it natively?

MQTT is the dominant IoT protocol for constrained devices, but industrial equipment — PLCs, SCADA systems, CNC machines — often communicates over OPC-UA, Modbus, or proprietary fieldbus protocols. AWS IoT Core and Azure IoT Hub support MQTT natively; they require custom translation layers for industrial protocols. ThingWorx and MindSphere support OPC-UA and industrial protocols natively. If your device fleet speaks a non-standard protocol, the integration cost of forcing it onto a platform that does not support it natively can exceed the entire rest of the project. Know your device protocol before evaluating platforms.

2. What is your anticipated message volume at peak device fleet scale, and what will it cost?

Platform economics change significantly as device fleets scale. A deployment of 500 devices sending data every 60 seconds generates roughly 720,000 messages per day. At AWS IoT Core pricing, that is modest. Scale to 10,000 devices sending data every 10 seconds and the message count reaches 86 million per day — a different cost category entirely. Per-message pricing platforms require careful message architecture to control cloud spend at scale. Per-device platforms (Particle) produce more predictable economics. Custom software with owned infrastructure eliminates the per-message cost entirely in exchange for infrastructure management overhead.

3. What operational systems does the IoT data need to connect to, and how?

IoT data that sits in a dashboard without flowing into the systems people use to run the business generates reports, not outcomes. Identify the specific systems the IoT data needs to reach: ERP for production reporting, CRM for service ticket generation, SCADA for control loop feedback, billing for usage-based invoicing, or maintenance management for work order creation. Then evaluate how each platform connects to those systems — native integration, generic webhook, or custom API development required. A platform with rich IoT capabilities but no practical path to your specific operational integration targets is not a solution for your use case.

4. Who will own the platform architecture after go-live?

IoT platforms are long-lived. The configuration decisions made at initial deployment — message routing rules, device shadow schema, data retention policies, alerting thresholds — become the foundation that every future change builds on. If those decisions are made by a consultant who leaves after deployment, or by an AWS engineer who designed the architecture but will not be available when the device fleet triples, the platform accumulates technical debt faster than the operations team can surface it. Every platform evaluation should include a question about ownership: who in your organization will be the keeper of the IoT system architecture two years from now, and does the platform's complexity match their capability?

5. How does the platform handle OTA firmware updates across a large device fleet?

Devices in production need firmware updates to fix vulnerabilities, add capabilities, and maintain protocol compatibility. A platform that does not include OTA update management — or that handles it as a manual process — leaves you responsible for updating every device individually as your fleet grows. Ask specifically: how does the platform stage firmware updates across a subset of devices before rolling to the full fleet, how does it handle partial update failures mid-rollout, and what happens to devices that are offline when an update is pushed. Platforms that have not thought through firmware lifecycle management become security liabilities as device fleets age.

The verdict

AWS IoT Core is the strongest foundation for engineering teams building cloud-native IoT systems on AWS who have the technical depth to architect the application layer from primitives. Azure IoT Hub is the clear choice for enterprises already on Microsoft 365 or Azure who need managed connectivity with native Defender and Power BI integration.

RaftLabs is the right choice when a mid-market business needs a production IoT platform — device management, real-time data pipelines, and operational system integrations — delivered at fixed cost by a team that owns the architecture from device to dashboard.

PTC ThingWorx is the strongest industrial IoT application platform for manufacturers who need OT protocol connectivity and an application development environment without starting from cloud infrastructure. Siemens MindSphere is the clearest choice for organizations with existing Siemens automation infrastructure who need to unlock operational intelligence from their factory floor.

IBM Watson IoT Platform is the best fit for enterprises already running IBM Maximo or IBM's compliance tooling who need IoT connectivity with native asset management integration. Particle is the most coherent solution for hardware product teams who want integrated device modules, managed cellular connectivity, and cloud management from one vendor. Losant is the fastest path to operational IoT dashboards for teams without cloud infrastructure engineering expertise.

The right IoT software is not the one with the most enterprise logos in its case studies. It is the one whose architecture matches your device types, your message volumes, your integration targets, and your team's capability to own the system after go-live.

RaftLabs builds production IoT platforms. 4.9/5 on Clutch. Talk to a founder about your build.