AI/GenAI Development • MILESTONE_BASED
Custom RAG Knowledge Bot & LLM Integration
Private document search and AI answering engine using vector embeddings.
Python
OpenAI API
ChromaDB/Pinecone
LangChain
Laravel
Pricing Model
Starting from
₹27,999
⏱️ Est. Timeline: 2-3 Weeks
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Direct requirement review by architects
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Transparent milestone-based breakdown
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Source code & setup documentation
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90-day standard support period
Service Overview & Architectural Scope
Integrate OpenAI, Claude, or local open-source LLMs into your software with Retrieval-Augmented Generation (RAG). Prevent hallucinations and protect private IP.
Core Deliverables & Engineering Scope
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Document parsing (PDF, DOCX, TXT, CSV)
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Vector similarity search with metadata filtering
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Prompt engineering with citation tracking
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Rate limiting, cost guards, and audit logs
Execution Milestones
1
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Chunking and embedding document corpus.
2
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Calibrating cosine similarity thresholds.
Frequently Asked Questions
Are my company documents kept private?
Yes, data is processed securely and never used to train public foundation models.
Ready to build?
Submit your project requirements, specify your expected delivery timeline, and our engineering team will provide a transparent proposal.