Data & Technology · Applied AI Engineering
LLMs, RAG and agents that survive enterprise reality.
We build production AI systems — not demos. Retrieval that stays accurate, agents that stay in control, and evaluation and guardrails that make it safe to ship into regulated, high-stakes environments.
Agentic RAG pipelineIN CONTROL
01 User query
Retrieve
Hybrid search + rerank
Vector
store
store
LLM + agent tools
Reasoning, tool calls, orchestration
✓
Guardrails & eval
Grounding checks before response
What we deliver
From prototype to production-grade AI.
01
LLM applications & copilots
Domain copilots and assistants embedded into real workflows, with the UX and controls to match.
02
RAG & knowledge retrieval
Grounded retrieval over your data — chunking, embeddings, re-ranking and citations that hold up.
03
Agentic systems & orchestration
Multi-step agents with tools, memory and orchestration — scoped, observable and controllable.
04
Evaluation & guardrails
Eval harnesses, quality gates, safety guardrails and human-in-the-loop review before go-live.
05
MLOps / LLMOps
Deployment, monitoring, prompt & model versioning, cost controls and drift detection in production.
06
Model strategy & tuning
Model selection, routing, fine-tuning and distillation to balance quality, latency and cost.
Stack & tools we work in
OpenAI
Claude
LangChainLlamaIndexLangGraph
pgvector
Pinecone
AWS Bedrock
Vertex AI
Hugging FaceThe AI-native difference
Powered by Praveg AI, delivered by Cyborg Teams.
Agentic SDLC
Plan, build, test, review, ship and operate — agents accelerate every stage, humans own the gates.
Safe by construction
Guardrails, evals and human review built in — so AI ships responsibly into real operations.
Reusable AI layer
Praveg AI gives a consistent operating layer across use cases, reducing delivery risk.
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