Technology Sector Consulting

Technology companies typically have strong internal engineering talent already, so the value Zonopact provides is usually focused expertise: multi-tenant architecture patterns, compliance evidence automation and AI product design, delivered alongside existing teams rather than replacing them.

We embed the logging, access control and change management practices SOC 2 requires directly into engineering workflows through DevSecOps Consulting, and use ZonalGuard360 to collect the evidence continuously so preparing for an audit does not require a separate manual effort each cycle.

SOC 2 is an attestation report, common in North America, that evaluates a company's controls against trust service criteria such as security and availability over a period of time. ISO 27001 is an international certification for an information security management system. Many enterprise buyers, particularly outside the United States, expect ISO 27001, while others accept either.

We pair AI Consulting with AI Governance so that every AI feature, whether customer-facing or internal, includes model evaluation, documented data handling practices and an audit trail before it reaches production, rather than being deployed without oversight.

Yes. We typically recommend incremental modernization, extracting specific services from a monolith as scaling pressure requires it, rather than a full rewrite that risks halting feature development for an extended period.

ZonalGuard360 gives engineering, security and product leadership a single view of compliance status across SOC 2, ISO 27001 and AI governance requirements, replacing the spreadsheets and scattered documentation many growth-stage companies rely on before an enterprise sales cycle or audit.

Multi-tenant architecture allows a single application instance to serve multiple customers while keeping their data isolated. Getting tenant isolation right affects security, performance and cost, and mistakes made early are expensive to correct once a platform has scaled to many customers.

Cost reduction typically comes from right-sizing compute resources, adopting autoscaling instead of static provisioning, optimizing data storage tiers and identifying underused services, work we deliver through Cloud Consulting alongside a reliability review.

We start with a discovery phase that evaluates where AI genuinely improves the user experience, then prototype using retrieval-augmented generation or agentic workflows where appropriate, and validate cost, latency and accuracy before a feature ships broadly.

Deals commonly stall when a vendor cannot produce a current SOC 2 report or ISO 27001 certificate, lacks documentation of data handling practices for AI features, or cannot answer specific questions about tenant isolation and incident response procedures.

We focus on removing friction: automating deployment approvals, reducing flaky test suites, paying down technical debt that slows every subsequent change and giving engineering leadership visibility into where time is actually spent.

Yes. We design and execute multi-region deployment strategies that improve uptime and reduce latency for global customers, sequencing the migration to avoid downtime for existing production traffic.

We commonly connect product usage data, billing data and support ticket data into a single analytics layer, giving customer success and product teams a unified view of account health instead of relying on separate systems that do not talk to each other.

A focused engagement, such as a SOC 2 readiness project or an AI feature prototype, typically takes two to four months. Larger initiatives such as a multi-region migration or a full platform engineering buildout usually run six months to a year depending on the scope of existing systems.