AI systems builtto hold upunder inspection.

I'm Sam Sankar, an AI/ML engineer building practical agent infrastructure, grounded evaluation environments, and research tooling that can be examined end to end.

01 / BASE

Virudhunagar, Tamil Nadu, India

02 / PRACTICE

AI systems engineering

03 / STATUS

Open to focused collaborations

Portrait of Sam Sankar wearing glasses and a tailored black suit

01 / SELECTED SYSTEMS

Works® 25—26

Open-source systems for agentic tooling, model evaluation, and reliable AI delivery—each presented with source evidence.

01

Agentic tool infrastructure

MaterialPilot

A local-first MCP bridge that lets AI agents inspect, create, validate, and export procedural material graphs.
Open ↗
02

LLM grounding & evaluation

HallucinationGuard-Env

An OpenEnv-compatible training and evaluation environment for factual grounding, citation discipline, calibration, and refusal behavior.
Open ↗
03

Multimodal reasoning

AEGIS

An interpretable deepfake-analysis pipeline using staged visual reasoning, self-critique, and contradiction-aware evidence aggregation.
Open ↗
04

Schema-driven application generation

Promptless Generator

A schema-driven application generator that converts database structure into a functional initial interface without requiring a natural-language prompt.
R&D / SOURCE NOTEOpen ↗
01143

typed MCP tools

02392

node definitions

031.09M

evaluation examples

0438

datasets

02 / PROFILE

From research prototype to dependable system.

Published HallucinationGuard environment overview.

My work connects the experimentation of applied AI with the discipline needed to operate it: typed boundaries, visible evidence, practical deployment paths, and explicit limitations.

The goal is not an impressive demo. It is a system another person can understand, test, and carry forward.

More about the practice ↗

03 / CAPABILITY MATRIX

Tools are only useful when the boundaries are clear.

Select a capability to trace how it appears in the published work.

SELECTED CAPABILITYMCP

Used in: MaterialPilot · HallucinationGuard

01 / Model engineering

02 / Agentic systems

03 / Infrastructure

04 / Applied AI

04 / EXPERIENCE TRACE

Independent research, built for real delivery.

2026
INDEPENDENT R&D / MAR—JUL

AI Infrastructure & MLOps Engineer

Built open-source AI systems across architecture, fine-tuning, evaluation, deployment, testing, and documentation.

2025
IT LINKS / INTERNSHIP / 10 DAYS

Full-Stack Web Development Intern

Delivered a bulk certificate-generation application from requirements through testing, debugging, and handoff.

05 / EDUCATION

Bachelor of Engineering

Computer Science and Engineering

AAA College of Engineering and Technology
2023—2027 expectedCGPA 7.8 / 10

06 / CERTIFICATION ARCHIVE

01

Oracle

OCI 2025 Certified AI Foundations Associate

02

Oracle

OCI 2025 Certified Foundations Associate

03

NPTEL

GPU Architectures and Programming

04

NPTEL

CPU Architecture

05

NPTEL

Industry 4.0 and Industrial Internet of Things

06

Google

Google Analytics Certification

07

MongoDB University

Connecting to MongoDB in Node.js

01

Inspectability

Intermediate evidence stays visible.

02

Local-first

Authority and data stay close to the user.

03

Reproducibility

Systems are documented, testable, and repeatable.

04

Clear limits

Unknowns are named instead of designed away.

07 / START A CONVERSATION

Let's build AI systems that hold up under inspection.

Virudhunagar, Tamil Nadu, India

English / Tamil

Email Sam ↗Open contact page ↗