IoT secure data platforms

Secure data platforms are the operational backbone of connected estates. Sensors and gateways generate RF and IP telemetry, but the real requirement is trust: proving what produced the data, how it moved, what changed, and who can access it. If you cannot prove those four things, you do not have a secure platform, you have a dashboard.

Squared Technologies specialises in building bespoke IoT platforms for high-assurance environments. We do not ship templates and we do not bolt security on at the end. We design the platform as a zero trust system from the first line of architecture: explicit identity, scoped permissions, secure transport, governed data contracts, and evidence-grade audit trails.

Zero trust starts at the edge. Devices, tags, gateways, services, and users must be uniquely identifiable. We implement strong device identity using certificate-based authentication and controlled onboarding, then enforce least-privilege access throughout the fleet. Transport is secured using mTLS where appropriate, with policy boundaries that prevent cross-tenant leakage as rollouts expand across sites and stakeholders.

The data plane is engineered for real-world telemetry, not lab conditions. RF and low-power estates produce bursty events, intermittent links, and noisy signals. Our pipelines are built for validation, idempotency, bounded retries, and backpressure so ingestion remains predictable during outages, reconnect storms, and operational change. Reliability is part of security because the first compromise is usually operational.

We build platforms end to end: ingestion, processing, storage, and customer delivery. For enterprise-grade deployments we typically use AWS services that align to assurance requirements: authenticated ingestion (AWS IoT patterns), streaming and enrichment, durable storage, time-series and state stores, governed APIs, and perimeter controls. Where residency and private networking matter, we design private service paths, key custody and rotation, and a complete audit trail for assurance.

For smaller or dedicated deployments we can deliver a leaner, sovereign stack without losing governance: a secure ingestion tier, a clear data model, Postgres for relational truth, object storage for evidence and history, and a hardened API surface with explicit access control. The same operating principles apply, only the footprint changes.

A secure platform becomes far more valuable when it supports predictive analytics and predictive maintenance. We build the platform so telemetry can be turned into features, baselines, and anomalies without corrupting the audit trail. That means time alignment, deterministic event schemas, and clear provenance. You can then run models for drift detection, threshold learning, failure prediction, and asset health scoring, and feed outcomes into workflows instead of dashboard theatre.

Our software delivery is modern, security-conscious, and built for long-life operation. Interfaces are typically React and TypeScript, supported by service layers in proven ecosystems. We select the right runtime per constraint: Java for durable service workloads, TypeScript for rapid iteration, Python where model workflows and tooling benefit, and hardened infrastructure-as-code for repeatability. The outcome is a platform you can operate for years, not weeks.

The result is simple: a secure IoT data platform that you can defend. It behaves predictably under stress, proves what happened through evidence trails, and delivers telemetry into customer systems without multiplying risk. That is what zero trust looks like in practice.