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Generative AI and private LLMs

Generative AI on your own cloud, with your data kept private

Secure RAG, copilots and private LLM hosting using Azure OpenAI Service, Amazon Bedrock or open models in your own tenancy.

Enterprise-grade securityNamed engineersAWS and Azure expertise
how it worksGenerative AI and Private LLMs
User
Gateway
Retriever
Private LLM
Answer

Generative AI and private LLM hosting for enterprises

Xpecto Cloud builds secure generative AI platforms that run inside your own cloud tenancy. We deploy Azure OpenAI Service, Amazon Bedrock or open-source models, build retrieval-augmented generation (RAG) on your documents, and add guardrails, identity and audit logging.

Problems we solve

We cannot send company data to public AI tools.
Private deployments inside your own cloud tenancy with no data leaving.
Answers are generic and sometimes wrong.
RAG grounds answers in your documents, with guardrails.
LLM costs are hard to predict.
Usage limits, caching and model routing keep spend in check.
Security and compliance teams are blocking us.
Identity, logging, content filters and audit trails are built in.

What you get with Generative AI and Private LLMs

Private LLM hosting

Open models on GPU servers or managed services.

RAG pipelines

Ingest, chunk and retrieve your documents.

Vector search

Fast semantic search at scale.

Copilots and agents

Internal assistants with approvals and tools.

Guardrails

Content filters, PII masking and policies.

Evaluation and monitoring

Quality, cost and abuse tracking.

Integration

Connect to CRM, ERP and knowledge bases.

Azure OpenAI and Bedrock

Managed model access inside your tenancy.

Who Generative AI and Private LLMs is for

Enterprises with sensitive data

Legal, finance and operations teams.

Support and knowledge teams

Faster answers from internal documents.

Product teams

Teams adding AI features to their products.

How we set you up

A structured path from first conversation to a secure, running platform, with your teams involved at every stage.

Define use casesWe pick high-value, low-risk use cases and agree what data the models may use.
Design the private stackWe design model hosting, retrieval, identity and logging inside your own tenancy.
Build RAG and guardrailsWe ingest your documents, build retrieval and add content filters and PII controls.
Evaluate and secureWe test accuracy, safety and cost, then complete security and compliance reviews.
Launch and monitorWe release to pilot users, track quality and cost, and expand with confidence.

Generative AI and Private LLMs: before and after

Public AI toolsPrivate generative AI by Xpecto
PrivacyData shared with third partiesData stays in your tenancy
AccuracyGeneric answersAnswers grounded in your documents
ControlNo policy or auditGuardrails and audit logs
CostUnlimited, unpredictable useLimits, caching and routing
IntegrationCopy and pasteConnected to your systems

More about generative ai and private llms

Your data stays within your environment, answers are grounded in your content, and usage limits keep cost predictable. We integrate assistants with your CRM, ERP and knowledge bases, and can pair them with custom models from our MLOps platform.

Run it on Azure, AWS or dedicated GPU servers, and secure it with cloud security and compliance. Explore AI applications at xpectoai.com.

Azure OpenAI ServiceAmazon BedrockOpen-source LLMsLangChainVector databasesKubernetesPrivate endpointsXpecto AI

Generative AI and Private LLMs FAQs

Yes. Models run inside your own cloud tenancy or servers, and your data is not used to train public models.

Retrieval-augmented generation lets a model answer using your own documents, which improves accuracy and lets you show sources.

Yes. We host open models on GPU servers or managed services, with scaling, monitoring and security.

We apply usage limits, caching, model routing and monitoring, and review cost every month.
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