US Legal Tech Platform
100K+ case documents indexed with citation-aware retrieval. Lawyers find relevant precedents with exact paragraph citations in seconds. Semantic search with BM25 reranking and jurisdiction filtering.
RAG Engineering — India
Outsource RAG Development to India — Enterprise Knowledge AI at 60-70% Lower Cost
Production RAG pipelines for US/EU enterprises. Indian engineering talent with deep retrieval and NLP expertise.
Get a RAG Architecture Plan✓ 60-70% cost savings✓ SOC 2-aligned✓ 20+ languages supported
Trusted by US, EU, and Global Enterprise Teams
Why Outsource RAG to India
Three Reasons to Build RAG in India
01
60-70% Cost Advantage
Senior RAG engineers in India cost 60-70% less than US equivalents. Same tools, same frameworks, same production standards — significantly lower burn rate for your AI budget.
02
Multi-Language RAG (20+ Languages)
Cross-lingual retrieval across European, Asian, and Indic languages. A query in French retrieves relevant English documents and vice versa. Essential for global enterprises.
03
SOC 2-Aligned Development
Enterprise-grade security practices. Code in your repos, deployment in your VPC, comprehensive NDAs and IP assignment. On-premise deployment with open-source LLMs when required.
What We Build
Enterprise RAG Systems Built from India
EU Compliance Knowledge Base
GDPR-aware retrieval system for a European fintech. Multi-language support across 8 EU languages. Regulatory document indexing with temporal awareness — always surfaces the latest applicable regulation.
Global HR Knowledge System
Unified HR knowledge base across 40 countries, 12 languages. Employees ask policy questions in their local language and get accurate, localized answers. Reduced HR ticket volume by 65%.
"Cartoon Mango was great to work with. They improvise and provide 24X7 support."— Gaurav Saxena, Media Manager, BCCI
Architecture
Our RAG Stack
Layer 1
Ingestion
Smart chunking strategies (semantic, recursive, parent-child). Metadata extraction for filtering. Support for PDF, DOCX, HTML, Markdown, Confluence, and custom formats.
Layer 2
Retrieval
Vector search (OpenAI, Cohere embeddings) + BM25 hybrid retrieval. Cross-encoder reranking for precision. Query expansion and HyDE for recall improvement.
Layer 3
Generation
Claude/GPT with citation-grounded prompts. Guardrails for hallucination prevention. Structured output with source references and confidence scores.
Layer 4
Evaluation
Automated relevance scoring, faithfulness checks, and hallucination detection. Continuous monitoring with human-in-the-loop feedback. Regression testing in CI.
20+
RAG Systems
60-70%
Lower Cost
vs US/EU development rates92%
Answer Accuracy
across production deployments20+
Languages
cross-lingual retrievalOur Process
From Corpus Audit to Production in 8 Weeks
Corpus Audit & Design
Analyze your document corpus, define chunking strategy, design retrieval architecture. Build evaluation dataset with your team. Timezone-aligned kickoff and planning.
→ RAG Architecture PlanPipeline Development
Build ingestion pipeline, vector store, retrieval chain, and generation layer. Weekly accuracy demos during your business hours with your evaluation dataset.
→ Working RAG PipelineOptimization & Integration
Tune retrieval quality, add guardrails, integrate with your existing systems. Load testing, security review, and edge case handling.
→ Production-Ready SystemDeploy & Monitor
Production deployment in your infrastructure with monitoring dashboards, alerting, and evaluation pipelines. 30-day support included.
→ Live DeploymentInvestment
Transparent Pricing (USD)
60-70% lower than US agency rates. Exact costs depend on corpus size and retrieval complexity — we provide a detailed estimate after the architecture audit.
PoC / Pilot
$5-12K3-5 weeksSingle-source RAG pipeline with evaluation. Prove accuracy on your corpus before committing to production build. Fixed scope and price.
Production System
$15-35K8-12 weeksMulti-source RAG with hybrid retrieval, reranking, guardrails, multi-language support, evaluation pipelines, and production deployment.
Enterprise
On RequestScoped per engagementMulti-tenant RAG platform with on-premise deployment, custom security, SOC 2-aligned processes, team training, and long-term support.
Contact UsWhy Us
Indian Engineering, Global Standards
Deep retrieval engineering expertise
20+ production RAG systems shipped. We know the difference between a demo that works on 10 documents and a pipeline that handles 100K+ documents reliably.
Evaluation pipelines from day one
Every RAG system ships with automated evaluation — retrieval relevance, answer faithfulness, and hallucination detection in CI. No guesswork on accuracy.
Enterprise security and IP protection
SOC 2-aligned processes, comprehensive NDAs, code in your repos, deployment in your infrastructure. We protect your IP as if it were our own.
FAQ
Common Questions
India has deep engineering talent in NLP, retrieval systems, and LLM application development. Our engineers work with the same tools (LangChain, LlamaIndex, vector databases, evaluation frameworks) as US teams. The difference is cost — you get 60-70% savings with equivalent technical depth. Many US companies already outsource RAG development to India for this reason.
We Have Delivered 100+ Digital Products
Sports and Gaming
IPL Fantasy League
Innovation and Development Partners for BCCI's official Fantasy Gaming Platform
Banking and Fintech
Kotak Mahindra Bank
Designing a seamless user experience for Kotak 811 digital savings account
News and Media
News Laundry
Reader-Supported Independent News and Media Organisation
Client Testimonials
What Our Partners Say
"Cartoon Mango was great to work with. They improvise and provide 24X7 support."
Gaurav SaxenaMedia Manager — BCCI
Tell Us About Your Knowledge Base Challenge
Share your document corpus and use case. We'll respond with a retrieval architecture plan, cost comparison, and timeline — not a sales pitch.
- RAG architecture assessment for your corpus
- 60-70% cost savings estimate vs US rates
- Engineering-first conversation, no fluff
Your information is secure. We never share your data.
