Enterprise RAG & Custom AI Systems
We engineer private Retrieval-Augmented Generation (RAG) engines, domain-adapted embedding pipelines, custom computer vision models, and streaming inference backends with strict citation accuracy.
Production AI Engineering
We don't build toy chatbots. We architect high-accuracy vector retrieval indexes, hybrid search rankings, semantic chunking algorithms, and anti-hallucination guardrails that return exact document citations.
Private Document RAG
Chunking, embedding, and vector storage for proprietary enterprise manuals, PDFs, and internal wikis.
Computer Vision & YOLO
Object detection, facial recognition, defect classification, and live video stream processing in PyTorch.
Streaming Inference APIs
FastAPI microservices supporting Server-Sent Events (SSE) token streaming under 150ms TTFT.
Evaluation Benchmarking
Ragas evaluation datasets measuring context recall, faithfulness, and answer relevance.
RAG Pipeline Architecture
- Semantic Chunking: Context-aware text splitters maintaining table structures and markdown headers.
- Hybrid Retrieval: Reciprocal Rank Fusion (RRF) combining dense vector embeddings with BM25 keyword matching.
- Cross-Encoder Reranking: Cohere or local BGE rerankers to filter low-relevance context before generation.
- Citation Verification: UI footnotes linking directly back to the source page and paragraph.
Scope Boundaries & GPU Provisioning
- • Custom model fine-tuning requires a verified dataset of at least 500 validated samples.
- • Vector database hosting costs (Pinecone, Supabase, or AWS OpenSearch) are provisioned under client billing.
- • Real-time video model inference requires dedicated GPU instances (e.g. AWS g4dn or GCP T4).
AI Engineering Stack
Have a Dataset Ready?
Send us your documents or computer vision requirements for an evaluation benchmark and prototype estimate.
Request AI ArchitecturePrefer Direct WhatsApp or Call?
Connect directly with our engineering team at +91 91461 99158 for immediate technical scoping, architecture advice, and transparent milestone pricing.