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Fiverr Pro
English
$
USD
I will build production rag and llm systems with guardrails
sandeshkale.ai
About this gig
I design and ship production GenAI software - RAG pipelines, LLM orchestration, and guardrails that stay accurate, auditable, and fast.
Who this is for:
- Product / engineering teams adding AI to an existing app
- Founders who need a real architecture, not a demo notebook
- BFSI / ops teams that care about reliability and reviewability
What you get:
- Clear architecture (router, retrieval, cache, guardrails)
- Working integration in your stack (Node/TypeScript, APIs, n8n where it fits)
- Typed contracts around model calls ? the model proposes, the system decides
- Handoff notes so your team can run it
Background: 10+ years BFSI / enterprise software. Independent builds include a market-analysis platform (Next.js + multi-provider LLM), a job-intelligence pipeline, and production B2B web apps. Certs: Confluent Kafka, DeepLearning.AI GenAI, GitHub Copilot GH-300. Portfolio: https://sandesh-portfolio-sable.vercel.app
Not included: unpaid full-product samples, off-platform payment before a Fiverr order, or guaranteed ranking claims.
Tell me your use case, stack, and deadline ? I will confirm scope before we start.
Get to know sandeshkale.ai
sandeshkale.ai
AI Automation Engineer n8n RAG and LLM Integration
- FromIndia
- Member sinceDec 2020
- Avg. response time1 hour
Languages
Marathi, English, Hindi
I design and ship production software for enterprises — especially GenAI systems that must stay accurate, auditable, and fast.
10+ years in BFSI/core systems (IBM BPM/BAW, open banking, AKS, AS400 bridges). Now focused on LLM orchestration, RAG pipelines, guardrails, and multi-agent workflows with typed contracts over model calls.
Independent builds: market-analysis platforms (Next.js/Supabase + multi-provider LLM cascade), job-intelligence pipelines, and production B2B web apps.
Based in Singapore. Portfolio: https://sandesh-portfolio-sable.vercel.app
My Portfolio
FAQ
What is included, what must I provide, and how do timeline and revisions work?
Scope is agreed before work starts: a production-ready GenAI/RAG/LLM implementation or architecture review. Please provide your goal, code/data/API access, and constraints. Typical timeline is 7–14 days. Includes production and guardrails thinking; 2 revision rounds are included.
