Turn Documents
to
Intelligence
Why Noesia
Built for teams who need RAG to actually work
Most RAG tools optimize for demos. Noesia optimizes for production — with evaluation, observability, and control at every stage.
Experiment First
Design, compare, and validate RAG configurations before production. Run side-by-side tests on chunking, embeddings, and retrieval.
Structured Pipelines
Explicit control over every stage — ingestion, chunking, retrieval, and reasoning. Every component is modular.
Evaluation Built-In
Metrics, scoring, and human feedback at every step. Know when quality degrades before users do.
Production-Ready
Low-latency APIs, governance controls, and deployment tooling from day one.
The Pipeline
Six Stages. Full Control.
Every component is modular, configurable, and independently testable.
Ingest
Documents & data sources
Index
Chunking & embeddings
Retrieve
Search & reranking
Reason
LLMs & context assembly
Eval
Testing & scoring
Serve
APIs & deployment
See How Intelligence Is Built
Configure pipelines, test retrieval strategies, and compare results in a workspace built for production teams.
Use Cases
Designed for Real AI Teams
From enterprise search to internal assistants — Noesia supports teams from prototype to production.
Enterprise Search
Ground answers in internal documents with relevance controls and full source traceability.
RAG Evaluation
Test pipelines against real queries. Compare quality across configurations before deployment.
Internal Assistants
Build assistants with source-aware responses your teams can actually rely on.
Platform Teams
Run modular, API-first workflows with clear ownership and full observability.
Works with your stack
Deploy Anywhere. Connect Everything.
OpenAI
Anthropic
Gemini
Ollama
vLLM
LiteLLM
ZAI
Qwen
BytePlus
QdrantOpenAIAnthropicGeminiOllamavLLMLiteLLMZAIQwenBytePlusQdrant
Supabase
pgvector
Google Cloud
AWS
Azure
Alibaba Cloud
OCI
Huawei Cloud
n8nSupabasepgvectorGoogle CloudAWSAzureAlibaba CloudOCIHuawei Cloudn8n