Platform243 helps financial institutions and enterprises architect secure, scalable, and AI-ready infrastructure — from cloud strategy to production ML pipelines.
Migrate, containerize, and automate your estate onto resilient cloud-native foundations — engineered for scale, uptime, and velocity.
Learn more — Infrastructure ModernizationRe-architect monoliths into cloud-native, event-driven services that ship faster, scale independently, and stay fast under load.
Learn more — Application ModernizationTurn scattered, untrusted data into governed, analytics-ready products — and the foundation your BI and AI actually need to be trustworthy.
Learn more — Data & AI ModernizationProtect cloud workloads, applications, and data end-to-end — proactive posture management, continuous monitoring, and rapid response.
Learn more — Cloud SecurityDeep experience inside Canada's largest, most regulated enterprises — we know what enterprise compliance and data governance actually means.
Strategy through to deployment. We don't hand you a slide deck — we build and ship production systems.
AWS, Azure, GCP — multi-cloud by design. We build for portability, not vendor lock-in.
Every engagement is designed with AI/ML extensibility in mind. Your data platform should power your models.
Cybersecurity is not a checkbox. It's baked into every architecture decision from day one.
Need senior technical leadership without a full-time hire? Platform243 can embed at the leadership level.
Migrated a monolithic data warehouse to a cloud-native lakehouse on Azure, reducing query latency by 94% and enabling real-time regulatory reporting.
Platform243 delivered what three previous vendors only promised. They shipped a production data platform our regulators were comfortable with — and our analysts actually love.
The rigour was unlike any consultant we had worked with. Every decision was documented, every control was evidenced. We passed SOC 2 Type II with zero exceptions.
They embedded as a fractional CTO and gave us senior technical leadership we could not have hired in time. Our ML models finally made it to production.
LLMs are only as good as the context you give them. Graph databases like Neo4j turn scattered enterprise data into connected, queryable context — grounding AI in relationships, not just text.
Databricks is no longer just managed Spark. With Delta Lake, Unity Catalog, and serverless compute, it has become a credible single platform for data engineering, analytics, and AI — if you adopt it with discipline.
Adopting Kubernetes is easy; operating it well is not. The enterprises that win treat it as the foundation for an internal platform — with golden paths, GitOps, and guardrails — not as an end in itself.
The warehouse-versus-lake debate is over. The interesting questions now are about governance, contracts, and treating data as a product.
Retrieval-augmented generation is easy to demo and hard to operate. Here is what production-grade RAG actually requires.
Zero trust is an architecture, not a product you can buy. A practical path from perimeter security to identity-aware access.
Let's talk about your cloud, data, or AI challenge. Discovery calls are free. Outcomes are guaranteed.