Stop burning millions onfragile AI infrastructure and broken agentic memory.
We help health-tech, fintech, and regulated enterprises achieve 90% cloud cost reductions and instantly deploy an air-gapped agentic memory layer—without the massive DevOps headache.
Built for Regulated Data
Designed for health-tech and fintech. Deploys directly into your secure, private cloud environment—no sensitive data ever leaves your VPC.
Flawless Context Management
Stops the DevOps drain. Your engineers focus on building autonomous agents and AI applications instead of wrestling with broken search pipelines and slow retrieval (9.6ms at 2,000+ QPS).
Sovereign AI Infrastructure
Deploys as code into your private cloud. Our natively optimized architecture powers your agentic memory layer, handling massive workloads while cutting enterprise cloud bills by up to 90% (e.g., $2.5M → $36K). No clusters. No third-party APIs. No data leaves your VPC.
POWERING AI ENGINES AT:
Shyftlabs
Dr Pal
Evalia AI
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Repello AI
99 Ravens AI
Why Legacy Context Pipelines Are Failing Your AI Agents.
Before we show you the fix, let's be honest about what's actually happening inside most enterprise AI stacks right now.
Bleeding Cash.
Burning $1M+ annually on bloated AWS/GCP vector databases and fragmented AI platforms. The cloud compute bill grows exponentially every time you add documents or scale your agents’ context window.
Sub-Par Quality & Hallucinations.
Struggling with broken agentic reasoning despite massive engineering efforts. Expensive re-rankers and heavy token-consuming patchwork can’t fix the wrong fundamentals—legacy ANN approximate search was simply never built for the agentic and compliance-grade context retrieval.
Maintenance Nightmares.
Engineering teams are trapped managing Kubernetes clusters, embedding pipeline patches, and fragile memory layers—instead of building the autonomous agents that actually move the business.
There is a better architecture. ↓
Powered by The Sovereign AI Stack.
Three steps. One sovereign pipeline. From empty cloud account to production-grade AI search — without a single cluster to manage.
Deploy.
Instantly provision a hermetically sealed, air-gapped AI stack directly into your private cloud using our Infrastructure as Code template. 400+ hardened assets. Online in under 10 minutes.
Compress.
Utilize our patent-pending Information-Theoretic binarization to optimize multi-modal ingestion, embedding, and storage — shrinking infrastructure loads by up to 90% while delivering deterministic, exact-match retrieval.
Build.
Access secure, native LLM models and agentic APIs to test and deploy applications instantly. No cluster management. No pager duty. No DevOps headache. Just ship.
Moorcheh vs. The Manual RAG Stack
| Metric | Moorcheh | The Manual RAG Stack |
|---|---|---|
| Auth & Multitenancy | Native. Ready on Day 1. (zero config, built-in) | Months of custom logic & security audits. |
| File Ingestion | Unlimited. 5 GB files, charts, audio & video. | Fragile parsers and "OOM" errors. |
| RAG Accuracy | Fully optimized. Tuned ingestion, retrieval & output. | Hard to get right, costly to fix. |
| Security | Air-gapped. Stays in your VPC. (zero external API calls) | High risk; data leaks via external APIs. |
| Model Support | Universal. One API for any LLM. (lowest inference cost available) | Constant re-engineering for every model update. |
| Maintenance | Zero-Ops. Updates & patches via IaC. | A dedicated DevOps team. (24/7 pager duty) |
| Idle Cost | $0. Truly scales to zero. | $10k+/mo. Fixed cluster overhead. |
| Total Value | Production in minutes. (400+ assets, one deployment) | $1M+ and 6 months of engineering debt. |
Proven Performance
Under the hood: Moorcheh uses Information-Theoretic optimization to achieve retrieval precision and infrastructure efficiency that traditional vector databases can't match. Consistently outperforms standard vector clusters by 40% in high-density multimodal environments.
Matches float32 systems despite 32× compression
vs 37–86ms (PGVector, Qdrant)
2,000 queries/sec sustained with no accuracy loss. No other system matches this.
End-to-end vs Pinecone + Cohere rerank
MAIR (Massive AI Retrieval) is an independent, large-scale benchmark that stress-tests retrieval systems across millions of documents, multimodal content, and concurrent query loads — the gold standard for validating production RAG infrastructure.
Sovereign AI Infrastructure.
Your VPC. Your Rules.
Moorcheh provisions a hermetically sealed, production-grade AI stack inside your cloud perimeter. Zero external API calls. Zero data leakage. 100% ownership. Ideal for regulated industries with strict data security requirements.
Stop settling for third-party wrappers that leak metadata. Moorcheh deploys a native, serverless factory into your AWS, GCP, or Azure account — the only architecture that combines 2,000+ QPS performance with an air-gapped security model that satisfies the most rigorous enterprise compliance audits.
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
Stop paying millions for infrastructure.Start shipping sovereign AI agents.
Deploy in 10 minutes. Cut cloud costs by 90%. No clusters, no pager duty, no lock-in.