Toronto, Canada
Harry Sivashankaran
Senior Solutions Engineer with 5+ years in telematics, APIs, and fleet operations. Focused on building real-world systems that improve efficiency, visibility, and decision-making.
Senior Solutions Engineer with 5+ years in telematics, APIs, and fleet operations. Focused on building real-world systems that improve efficiency, visibility, and decision-making.
I work at the intersection of transportation and software.
Over the past 5+ years, I’ve worked in telematics and fleet technology, helping businesses integrate data, deploy camera programs, and build scalable systems for operational teams.
I'm especially interested in AI infrastructure for fleet operations: computer vision, enterprise workflows, and the platform layer that makes those systems useful in the field.
Concepts and workflows for in-cab and road-facing cameras that use computer vision to detect risk, coach drivers, and surface the right events for safety teams.
Developing an MCP that turns telematics, camera, and operational data into AI-ready tools so enterprise fleets can bring platform development into everyday workflows.
Computer vision for yards and terminals to detect trailer movement, unauthorized activity, and operational bottlenecks across high-volume fleet environments.
Lead SE on strategic accounts across enterprise, federal, and state/provincial segments. Own the full technical arc from discovery through proof-of-concept through signed contract, with particular depth in camera programs, computer vision safety workflows, and AI-enabled platform use cases that have to hold up in real fleet operations.
Scope deployments across telematics, dash cams, CV/ADAS, and safety workflows. Design POCs that validate event quality, video workflows, latency, and operational fit before a contract is signed.
Build bespoke demo environments with real vehicle, camera, and operational data so buyers can see how AI-assisted workflows would behave inside their own fleet, not in a generic sandbox.
Author responses to complex government and enterprise RFPs. Run on-site POCs with field operations and safety teams, collecting signal that shapes both the deal and the product roadmap.
Develop MCP-driven approaches that expose telematics, camera, and fleet data to AI systems. Advise customers on the platform architecture needed to bring enterprise AI into operational workflows.
Advised provincial ministries, municipalities, and transit agencies through fleet modernization, P3 procurement, and smart-mobility strategy. Built the case for multi-decade infrastructure decisions with a technical architecture layer most consultants couldn't provide.
Advised major Canadian transit agencies on digital transformation — asset management platforms, operations analytics, and connected-vehicle roadmaps.
Supported public-private partnership procurements: scoring vendor capability, sizing risk, and stress-testing technology assumptions on the technical evaluation side.
Built strategy and technical architecture for ministries planning multi-decade shifts toward connected, autonomous, and low-emission fleets.
Translated agency operational needs into vendor-ready requirements documentation, evaluation frameworks, and multi-year technology roadmaps.
My academic work complements the hands-on side of building for fleets, especially where software systems, AI, and operational decision-making overlap.