Information-TheoreticSearch Enginefor RAG & Agentic Memory
Production-grade semantic search that gets smarter as your data grows—with zero infrastructure overhead.
POWERING AI ENGINES AT:
Shyftlabs
Dr Pal
Evalia AI
Cardea Health.png)
Repello AI
99 Ravens AI
What Our Customers Say
At ShyftLabs, we prioritize engineering excellence and scalable infrastructure. Transitioning our vector search workloads to Moorcheh.ai has been a significant win, enabling us to scale to millions of documents while maintaining high retrieval quality and consistently low latency. Their self-hosted private cloud deployment fits perfectly with our security requirements, and their support team has been excellent in ensuring seamless updates and upgrades. Moorcheh.ai provides a sophisticated, cost-effective solution that truly delivers on better engineering.
Shobhit Khandelwal
Founder & CEO · Shyftlabs
What sets Moorcheh apart for us is the combination of high-performance semantic search with robust RAG support, all at a very competitive cost. The system delivers fast, accurate retrieval that scales easily as our data grows, and its cost-effective design means we're not paying excessive fees for infrastructure or compute.
Dr. Navid Khosravi
Founder · Evalia.ai
Implementing Moorcheh's RAG system transformed how DrPal interacts with users. The retrieval-augmented generation setup was incredibly fast, highly reliable, and significantly more contextually accurate than anything we'd used before. The seamless integration and performance improvements meant our responses were not only delivered faster, but were also much more dependable and grounded in the underlying data. Moorcheh's technology has been a strategic advantage for DrPal's conversational AI, and we're genuinely impressed with the results.
Dr. Ali Bostani
Founder · DrPal
Moorcheh vs. Traditional Vector Databases
| Metric | Moorcheh | Traditional Vector DBs |
|---|---|---|
| Input | Auto File Ingestion (up to 100 MB/file) | BYO (limited support) |
| Write Latency | Instant (Transform) (no build time) | Slow (Graph Build) (re-indexing lag) |
| Real-Time Data | Native Support (streaming ready) | Re-indexing Lag (consistency delay) |
| Architecture | Index-Free (pure transform) | HNSW Graph (heavy build) |
| RAG Built-in | Yes + Bedrock (closed VPC ecosystem) | No (BYO) (calling external API) |
| VPC Deploy | Cloud-Native (auto-scaling microservices) | Cloud-Hosted (large RAM, manual scaling) |
| Idle Cost | $0 | Always-on |
Proven Performance
Matches float32 systems despite 32× compression
vs 37–86ms (PGVector, Qdrant)
End-to-end vs Pinecone + Cohere rerank
at 1,000+ RPS with no degradation
Native VPC Deployment. Full Infrastructure-as-Code.
Don't just host a container. Provision a fully architected, serverless stack inside your own AWS, GCP, or Azure accounts.
Moorcheh integrates deeply with your cloud provider's native ecosystem. We provide production-ready AWS CDK constructs and Terraform templates that provision the entire semantic engine using native services. You get the scalability of serverless with the data sovereignty of a private VPC—with zero operational overhead.
Implementation Patterns
Practical implementation guides — deploy memory-augmented agents using Python, n8n, and the Console.
System Architecture: The MIB Engine
CTO Dr. Majid Fekri breaks down the Information-Theoretic architecture behind the sub-20ms retrieval engine.
MUMLA Demo
Building the memory that AI agents wish they had.
AI Agent
AI agents that reason, plan and act to accomplish goals.
OpenClaw Architecture and Memory System
Watch OpenClaw Architecture and Memory System.
Moorcheh.ai Enterprise Solution
Moorcheh.ai Enterprise solution on AWS Cloud using Terraform.
Building a Semantic Code Assistant
Implement a RAG pipeline in a Notebook to search technical documentation using the Python SDK.
Scientific Discovery with LangChain
Integrating Moorcheh with LangChain to build specialized research agents for academic papers.
The Unified RAG API: Walkthrough
A technical overview of the /answer endpoint: reducing complex RAG chains into a single HTTP request.
Vertical AI: Legal Due Diligence
Automating high-stakes document analysis and retrieval for the legal sector.
End-to-End Service Agent
Deploying a production-grade support agent trained on proprietary PDF documentation.
Rapid Prototyping in Console
From raw data ingestion to a functional semantic search prototype in minutes.
Start ArchitectingBuild the next generation of agentic AI
Moorcheh's unified semantic infrastructure — accurate, affordable, automatic.