LET'S BUILD
AI PRODUCT OWNER

I BUILD
AI PRODUCTS
THAT TURN
COMPLEXITY
INTO POSSIBILITY.

I'm Pranesh — an AI Product Owner building AI capabilities for life sciences, taking ideas from workflow to working prototype.

VIEW WORKLET'S BUILD TOGETHER
SCROLL DOWN ↓
02 / THE POINT OF VIEW

TECHNOLOGY IS INTERESTING.
WHAT PEOPLE DO WITH IT
IS MORE INTERESTING.

03 / SELECTED BUILDS

THREE
THINGS
I BUILT.

Interactive AI product prototypes exploring reasoning, retrieval, and document creation.

01 / REASON02 / RETRIEVE03 / CREATE
01 / REASON
GENAI CONTRACTING ASSISTANT / CLAUSE ANALYSER
Risk
detected.
HIGH RISKCLAUSE 7.2SOURCE VERIFIED
UNFAVOURABLE LIABILITY LANGUAGE

AI analysis grounded in source documents. Retrieve evidence → explain risk → regenerate terms.
RISK / NEGOTIATE / ANALYSEGenAI Contracting Assistant
EXPLORE PROJECT ↗
02 / RETRIEVE
SOP
LIBRARY
QUESTION
SOURCE
CONTEXT
ANSWER
KNOWLEDGE / SEARCH / RAGGenAI SOP Assistant
EXPLORE PROJECT ↗
03 / CREATE
AI DOC AUTHOR / DRAFT MODE

Write the
first draft

GENERATE STRUCTURE

USE CONTEXT

REFINE WITH AI
AUTHOR / STRUCTURE / REFINEAI Doc Author
EXPLORE PROJECT ↗
04 / HOW I BUILD

FROM
problem
TO prototype.

I enjoy understanding the core business problem, shaping the workflow, architecting the RAG pipeline, and building functional AI prototypes.

01

DISCOVER

Client pain points
Business workflow
Gaps & opportunities

02

FRAME

Product thinking
AI feasibility
Workflow design

03

PROTOTYPE

UI / UX
AI interactions
Working concepts

04

SHIP

PRD → Jira
Agile delivery
Testing / UAT

05

LEARN

Adoption
Change management
What's next?

05 / THE LAB

WHAT IF
AI COULD
build this?

Give the lab a product problem. It will turn your prompt into an actionable 5-step AI product flow.
PRODUCT PROTOTYPING MACHINE / 001
GENAI PRODUCT FLOW GENERATED
06 / WHY AI?

EVERYONE
DESERVES
A JARVIS.

AI removes the friction between intent and execution. It makes humans more capable and lets an individual take an idea from workflow to working software.

JARVIS // HUMAN CAPABILITY SHOULD EXPAND.
07 / THE PERSON

HOW I GOT
HERE.

2023

IIM JAMMU

MBA — Strategy & Analytics. Industry Interaction Cell. Hosted corporate seminars and leadership conclaves.

2023 / EXCHANGE

SOLBRIDGE

Selected for Student Exchange Program at SolBridge International School of Business, South Korea.

3+ YEARS

AI PRODUCT

Building AI products for life-sciences clients across discovery, solution design, RAG architecture, UAT and adoption.

NOW

BUILDING

Prototyping, experimenting, and bringing AI products from vision to working code.

🔍ESC
GenAI Contracting Assistant
Clause risk scoring & RAG clause retrieval
01 / REASON
GenAI SOP Assistant
Graph RAG knowledge engine & SOP search
02 / RETRIEVE
AI Doc Author
Multi-agent regulatory & clinical document drafter
03 / CREATE
Product Prototyping Machine
Interactive 5-step AI product flow generator
PLAYGROUND

SIGN IN TO LAB 👤

Access exclusive AI prototype sandboxes, PRD templates, and prototype demos.

01 / REASON

Contract Liability & Clause Analyser

Problem & Impact

Enterprise legal teams spend hundreds of hours manually verifying vendor contracts against internal liability guardrails. This tool automatically retrieves relevant clauses, flags risky indemnification language, and generates grounded counter-proposals.

Key Capabilities

• Automated Clause Risk Scoring (High/Medium/Low)
• Citation-backed source document retrieval
• Guardrail-aligned contract term re-generation
• Audit trail logging for compliance review
AI Product Owner & Prototyper
Enterprise Contracting / Life Sciences
Python, RAG, Vector Search, LLM Agents, React
Reduced initial clause review time by 68%

System Architecture & Knowledge Retrieval

Documents are parsed into semantic chunks and stored in a vector index with metadata filtering. Query processing runs dual-stage retrieval: dense vector similarity followed by reranking against internal GxP compliance guidelines.

Product Impact & Business KPIs

Contract Review Effort

Measured reduction in review effort after introducing the GenAI Contracting Assistant.

Before AI100%
After AI37.5%
↓ 60–65% Reduction in Contract-Review Effort

From Capability to Adoption

Production adoption and retention of the GenAI Contracting Assistant.

89%
Adoption
~550 active users
97%
Retention
Long-term active usage
~550 Active Users • 89% Adoption • 97% Retention