Reasoning
Mathematical, STEM and multi-step problem solving.
About Predictive Data Solutions
Rigorous intelligence for problems that matter.
PDS combines mathematics, data science and modern AI to turn difficult real-world questions into testable, practical solutions.
The practice
From complex information to reliable decisions.
Predictive Data Solutions is an applied intelligence practice working across Generative AI, AI evaluation, predictive analytics, mathematical modeling, signal intelligence and decision intelligence.
Our work begins with the problem—not a predetermined tool. We structure the evidence, choose rigorous methods and validate whether the result can be trusted in practice.
Current focus01 02 03 04
Can an AI system solve the problem it appears to solve?
PDS develops evaluations that distinguish genuine capability from plausible-looking output.
Reliability
Robustness, constraint following and reproducibility.
Agents
Planning, tool use, recovery and end-to-end outcomes.
Evidence
Failure analysis, benchmarks and grounded evaluation.
Founder and CEOView LinkedIn profile
Dr. Arun Kumar Parayatham
Dr. Arun is a mathematician and distinguished data scientist with more than 25 years of experience across AI, machine learning, predictive modeling, mathematical modeling and technical education.
His career spans enterprise AI architecture, private and local LLM systems, model evaluation, healthcare and financial intelligence, predictive platforms, and research-led talent development. His approach brings formal reasoning and quantitative rigor to modern AI—particularly the evaluation of reasoning, tool use, reliability and complex generated solutions.
25+years in applied AI and data science
2granted US patents
300+postgraduate students mentored
GenAI and AI evaluation experience
Building AI systems—and testing whether they truly work.
Dr. Arun’s current work connects deep mathematical reasoning with hands-on GenAI architecture, model development and systematic evaluation.
LLM reasoning and STEM assessment
Designing difficult, multi-step mathematical problems, reference solutions and expert validation methods to measure correctness, logical consistency and robustness.
Mathematics · STEM · Long-horizon reasoning · Failure analysisBenchmarks, training data and failure modes
Developing high-quality evaluation and training samples, identifying edge cases, and separating genuine problem-solving capability from pattern matching or plausible output.
Rubrics · Human feedback · Alignment · ReproducibilityPlanning, tools and constraint adherence
Assessing whether agents choose tools appropriately, follow instructions, recover from failure, use evidence correctly and complete dependent workflow steps.
Planning · Tool use · Recovery · Grounded outcomesPrivate LLM platforms and fine-tuning
Architecting private and on-premise LLM solutions using Llama, Qwen and Mistral families, with domain adaptation through LoRA, QLoRA and supervised fine-tuning.
Local LLMs · Model selection · LoRA · QLoRA · SFTGPU serving and scalable inference
Designing H100/A100 compute environments and optimized model-serving systems using vLLM and TensorRT-LLM, including high-availability and load-balancing considerations.
H100 · A100 · vLLM · TensorRT-LLM · ScaleFrom GenAI strategy to production architecture
Leading technical solutioning, architecture reviews and enterprise GenAI platform development, including a production offering associated with 40%+ productivity gains.
Architecture · Privacy · Safety · Authentication · DeliveryResearch and recognition
Mathematical depth. Applied AI leadership.
A career grounded in nationally recognized mathematical research and translated into practical AI systems, intellectual property and technical leadership.
NBHM PhD and Post-Doctoral Fellowships
Awarded through national competition by the National Board for Higher Mathematics, Department of Atomic Energy, India.
Two granted US patents
Patented work in reliable pattern discovery and parallel discretization of continuous variables.
PhD in Mathematics
Differential geometry and complex manifolds, supported by an MTech in Computer Science and advanced mathematics degrees.
UGC JRF and NET
Junior Research Fellowship and National Eligibility for Lectureship in mathematical sciences.
Enterprise AI and GenAI
Architecture and advisory leadership across LLM systems, AI platforms, predictive analytics and model evaluation.
300+ postgraduate mentees
Long-term contribution to research-oriented AI, machine-learning and data-science education.
Our philosophy
Understand. Structure. Validate.
“Turn difficult problems into understandable structures, transform data into reliable intelligence, and build solutions that make a real difference.”
Work with PDS