YagnoTech Inc. helps organizations move from AI ambition to production capability with governed data platforms, privacy-first AI pipelines, and cloud infrastructure built for reliability, auditability, and scale.
From strategy and governance to production delivery, we help organizations modernize critical data systems with senior technical execution.
Assess data maturity, identify high-value AI use cases, and define practical roadmaps for LLM, analytics, and automation initiatives that can survive real enterprise constraints.
Design AI and data platforms with access control, lineage, auditability, privacy safeguards, and operating patterns that make advanced analytics trustworthy at scale.
Architect lakehouse, warehouse, and analytics platforms on Azure, AWS, and GCP using modern patterns across Databricks, Synapse, Fabric, Redshift, Glue, Athena, and BigQuery.
Move legacy warehouses, Hadoop estates, SaaS reporting layers, and on-prem pipelines into resilient cloud architectures with disciplined migration planning and continuity controls.
Build observable ETL and ELT pipelines using Azure Data Factory, Apache Spark, Airflow, AWS Glue, Talend, and Informatica, with reliability and governance designed in from the start.
Provide senior architecture reviews, stack selection, delivery planning, and cross-functional alignment between engineering, analytics, legal, compliance, and leadership teams.
Evidence of delivery across regulated, high-scale, and operationally sensitive environments.
Challenge: Modernize legacy on-prem data flows for a regulated financial institution. Delivery: Built governed AWS data warehouse capabilities with PII anonymization, SCD-1/SCD-2 modelling on Redshift, and executive Tableau reporting. Impact: Improved the foundation for trusted analytics and cloud-scale reporting.
Challenge: Support a province-wide data warehouse redesign tied to driver licensing data for millions of British Columbians. Delivery: Delivered high-performance ETL pipelines on Hadoop and contributed to hybrid migration planning. Impact: Helped strengthen a critical public-sector data foundation.
Challenge: Improve reliability, compliance reporting, and delivery speed for a global music data platform. Delivery: Executed 10+ zero-downtime database migrations, improved data delivery performance by 30%, automated deployments with Terraform, and produced 100+ DSRF compliance reports. Impact: Reduced operational risk while improving platform velocity.
Challenge: Support enterprise analytics, privacy, and data transformation across driver licensing and road safety programs. Delivery: Built contravention analytics pipelines, implemented data masking and lineage programs, and supported the RAAP driver-based insurance model transformation. Impact: Enabled governed analytics for sensitive, public-facing systems.
We bring the mindset of builders to every consulting engagement.
A modern digital dining platform connecting restaurants with customers, built to streamline menus, ordering, operations, and customer insight through practical data-driven technology.
Clear governance, practical milestones, and senior execution from discovery through production handover.
We clarify business goals, data landscape, compliance constraints, stakeholders, risks, and expected outcomes before recommending a path forward.
We define the target architecture, delivery phases, governance model, milestones, and commercial structure with enough detail for confident decision-making.
We deliver in focused cycles with regular demos, technical documentation, observability, and risk management built into the engineering process.
We complete production readiness, knowledge transfer, documentation, and post-launch support so internal teams can operate with confidence.
YagnoTech Inc. is a Canadian technology consulting firm focused on enterprise AI engineering, governed data platforms, cloud modernization, and privacy-first architecture. Our work sits where technical execution, compliance, and business-critical delivery meet.
The firm is led by Karan Tongay, who holds an MSc in Computer Science with a focus on data privacy from the University of Victoria, is a published IEEE researcher, and carries AWS and Microsoft certifications. His work spans differential privacy, LLM integration, cloud migrations, and large-scale ETL across Azure, AWS, and GCP.
We engage as senior technical partners for organizations that need more than implementation support: clear architecture, accountable delivery, executive-ready communication, and systems that can be operated after launch.
Meet Karan →If your organization is modernizing data infrastructure, evaluating enterprise AI, or building privacy-first analytics capabilities, YagnoTech can help shape the architecture and deliver the work.