AI-powered decision support system using existing Large Language Models -- 2
Budget: ₹250,000 – ₹500,000 INR
I wanted someone To build a secure, private AI-powered decision support system using existing Large Language Models (LLMs) that enables fast information retrieval, financial analysis, eligibility assessment, competitive intelligence, and strategic bid decision-making, based on internal company data and curated competitor intelligence.
We are looking to engage an experienced freelancer to design and build a Private Enterprise AI Decision Support System using existing LLM models (no model training from scratch).
Scope of Work:
Build a secure AI system using existing LLMs (GPT / Llama / Mistral, etc.)
Implement RAG-based document intelligence over company data (financials, bank statements, tenders, work orders, certificates)
Develop decision-support capabilities (bid/no-bid, eligibility analysis, financial insights)
Create a competitor intelligence module to identify probable bidders and analyze historical bidding behavior
Ensure data security and explainable outputs
Key Requirements:
Strong hands-on experience with LLMs, RAG, and vector databases
Experience building enterprise or decision-intelligence AI systems
Ability to deliver a working MVP in 4–6 weeks
Comfortable working with confidential financial and government-project data
Preference will be given to freelancers who have previously built similar LLM-based enterprise decision or competitive intelligence systems.
Engagement Type: Freelance / Contract
Duration: Short-term (Phase-1)
Start: Immediate
We are looking to engage an experienced freelancer to design and build a Private Enterprise AI Decision Support System using existing LLM models (no model training from scratch).
Scope of Work:
Build a secure AI system using existing LLMs (GPT / Llama / Mistral, etc.)
Implement RAG-based document intelligence over company data (financials, bank statements, tenders, work orders, certificates)
Develop decision-support capabilities (bid/no-bid, eligibility analysis, financial insights)
Create a competitor intelligence module to identify probable bidders and analyze historical bidding behavior
Ensure data security and explainable outputs
Key Requirements:
Strong hands-on experience with LLMs, RAG, and vector databases
Experience building enterprise or decision-intelligence AI systems
Ability to deliver a working MVP in 4–6 weeks
Comfortable working with confidential financial and government-project data
Preference will be given to freelancers who have previously built similar LLM-based enterprise decision or competitive intelligence systems.
Engagement Type: Freelance / Contract
Duration: Short-term (Phase-1)
Start: Immediate