Sanket Rajeev Sabharwal, Co-Founder of Algorithmic
CO-FOUNDER

Sanket Rajeev Sabharwal

PhD in Computer Science (ML and computer vision) from the University of Genoa. Published in IEEE Access and Nature Scientific Reports. Former Deloitte senior analyst. Both founders are embedded in every engagement, owning delivery end-to-end across product builds, ML systems, and data platforms.

Articles

A brass admission box full of plain ticket stubs with a single gold ticket on top, illustrating the value moment in customer analytics.
A closed brass padlock with its key resting just out of reach, illustrating a build versus buy decision that prices the exit path and vendor lock-in.
An archery target with a tight cluster of darts before a wall of blank gauges, illustrating AI production readiness beyond model accuracy.
Brass calipers measuring a precision-machined metal part on a workbench, illustrating how to vet a software agency using delivery evidence before signing.
Brass universal travel adapter with multiple plug types, illustrating AI vendor lock-in and LLM API migration paths.
A brass block fitting a wooden shape-sorter, illustrating LLM integration patterns that enforce typed contracts on model output.
An ornate brass cash register, illustrating ML monitoring that prices each failure type by its real cost.
A yellow canary in a brass birdcage beside a tuning fork, illustrating canary releases and rollback discipline in LLM fine-tuning.
A brass balance scale weighing one gold weight against many coins, illustrating how to scope software around business decisions.
Brass centrifugal governor with spinning weighted balls, illustrating AI agent governance and SLAs for production write access.
Brass gate valve on a steel pipeline, illustrating CMS and low-code deployment controls and release gating for production systems.
A steel chain with one weaker link, illustrating production readiness reviews that find failure modes before launch.
Stepping stones across a surface with one set apart, illustrating SaaS retention and the workflow step where users drop off.
An app interface card multiplying into duplicate versions, illustrating custom feature forks and SaaS product debt.
Senior leaders reviewing architecture and governance to choose between a data warehouse and a data lake before vendor selection.
Enterprise team reviewing camera provenance, dataset rights, and audit evidence for enterprise computer vision procurement.
Senior architect reviewing structural blueprints, illustrating the false economy of a quick MVP without sound architecture.
Engineer adjusting control-panel dials, illustrating hyperparameter optimization and tuning for machine learning performance.
Team reviewing architecture diagrams on a whiteboard, illustrating the software development lifecycle for founders and product leaders.
Person arranging mixed photos, charts, and reports, illustrating the multimodal gap in enterprise AI and multimodal RAG.
Engineer reviewing structured data features on screen, illustrating how feature engineering decides machine learning outcomes.
Team reviewing a machine learning readiness checklist covering data quality, infrastructure, and ROI.