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I will architect a scalable rag system with ai integration
Bheemesh M
About this gig
Welcome to Architecton AI Solutions. We specialize in transforming fragmented enterprise data into a 'Single Source of Truth' for Generative AI.
Led by a Solution Architect with 17+ years of experience in Data Engineering and 10 years in Machine Learning, we build RAG (Retrieval-Augmented Generation) systems designed for accuracy, security, and zero hallucinations.
Our RAG Architectural Expertise:
- Data-First Foundation: We leverage deep expertise in SQL, PL/SQL, and ETL (Informatica) to build robust pipelines between your relational databases and vector stores
- Advanced Retrieval: We implement semantic search, metadata filtering, and re-ranking using Pinecone, Weaviate, or Azure AI Search.
- Enterprise Security: We architect with a 'Security-First' mindset, utilizing Azure Key Vault for secret management and ensuring RBAC compliance.
- Hallucination Mitigation: We use advanced grounding techniques to ensure your LLM (GPT-4, Claude, or Llama) only responds based on your verified corporate data.
Why Partner with Architecton AI? We don't just provide code, we provide architectural blueprints that align with global IT standards. Whether you need to talk to your documentation or
Get to know Bheemesh M
Bheemesh M
Principal AI Architect Enterprise GenAI, Agentic Workflows
- FromIndia
- Member sinceMar 2026
- Avg. response time1 hour
Languages
English
Architecton AI Solutions is a premier consultancy led by a Principal Architect with 18+ years of technical leadership in Global Tier-1 IT Consulting and Fortune 500 Systems Integration. We specialize in bridging the gap between legacy enterprise data and modern autonomous ecosystems. Our guiding principle is Architectural Rigor: we do not build simple 'chatbots', we engineer sustainable, hallucination-resistant, and production-ready AI engines.
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FAQ
How do you ensure the RAG system doesn't "hallucinate"?
As a Solution Architect with over 10 years in ML, I implement advanced 'Grounding' techniques and metadata filtering. This ensures the LLM only generates responses based strictly on your provided enterprise data
Can you integrate this with my existing SQL or Oracle database?
Yes. I have extensive experience in SQL, PL/SQL, and ETL Informatica. I specialize in building the data pipelines necessary to sync your relational databases with vector stores for real-time AI retrieval.
Which LLMs do you work with for RAG?
I primarily architect solutions using Azure OpenAI (GPT-4), AWS Bedrock (Claude/Llama), and open-source models through LangChain and Haystack.
Is my data secure during the retrieval process?
Security is my priority. I design architectures that utilize Azure Key Vault for secret management and ensure that data is processed within your secure cloud perimeter.
Do you provide documentation for the architecture?
Yes. Every project includes a technical overview. For Premium tiers, I provide a full Architectural Blueprint suitable for internal IT stakeholder reviews.
