Most founders are sitting on a goldmine of documents they can't actually use.
Contracts buried in folders. SOPs nobody reads. Research reports that took weeks to produce — answered with "I think it was in the Q3 doc somewhere."
I'm building DocMind — an AI-powered document intelligence system that lets you talk to your entire document library.
Upload your PDFs, contracts, reports, wikis. Ask questions in plain English. Get precise answers with source references — not hallucinations, not summaries, actual answers pulled from your documents.
What's under the hood:
→ RAG pipeline (retrieval-augmented generation)
→ Semantic search across your entire doc library
→ Source-cited responses so you know exactly where the answer came from
→ Built for founders who can't afford to lose critical knowledge inside files
Nearly done building. Looking to connect with founders, ops leads, or teams managing large volumes of internal documents who want an early look.
I've built a new mobile AI assistant that brings chat, text and image generation, voice input and document analysis into one app.
It have Smart Chat, Text Creator, Image Create, Voice Input, plus PDF Scanner, Photo Analyze, Social Content and Prompt Ideas, filtered by category.
Almost everything AI can do, just in one place.
Designed LeadAI, an AI-powered prospecting SaaS platform built around lead discovery, campaign management, sales automation, AI workflows, and subscription management.
My approach combines strategic UX thinking with modern SaaS UI systems to make complex product workflows feel simple, intuitive, and scalable.
Designing lead prospecting flows that don't feel overwhelming is super tough, but this layout nailed it! As a full-stack engineer who builds AI agent workflows, seeing a UI that cleanly structures multi-step AI tasks and credit limits is super inspiring. Top-tier execution, Shasanko!.
𝐑𝐀𝐆 𝐀𝐈 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 | 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐒𝐞𝐚𝐫𝐜𝐡, 𝐀𝐈 𝐀𝐧𝐬𝐰𝐞𝐫𝐬 & 𝐕𝐞𝐜𝐭𝐨𝐫 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞
I designed and built a RAG-powered AI knowledge platform that lets businesses search documents, websites, databases, and internal knowledge using natural language.
The system processes content, creates embeddings, stores them in a vector database, retrieves the most relevant information, and uses AI to generate accurate, source-grounded answers.
My services include: RAG development, document ingestion, semantic search, vector database setup, OpenAI/LLM integration, internal knowledge assistants, API integrations, and analytics.
The solution helps teams find information faster, reduce repetitive research, improve answer consistency, and build scalable AI-powered knowledge systems.