Sensitive data leaves the organization
Employees may paste customer records, contracts, or internal plans into systems the company does not govern.
Secure AI infrastructure for growing businesses
Private AI for
Your Business
Your data. Your infrastructure. Your AI.
Deep Conduit designs, deploys, and manages locally hosted AI systems that give employees a familiar chat experience while keeping proprietary company information under your control.
PRIVATE AI ENVIRONMENTControlled
Simple employee experienceAsk questions. Find information. Complete work.
↓ authenticated request
IDENTITY + POLICY GATESSO · Role-based access · Least privilege
↓ authorized context only
KNOWLEDGEDocuments + systems
WORKFLOWSApproved tools + agents
MODELSLocal LLM inference
OPERATIONSMonitoring + evaluation
Runs on infrastructure your organization controls
Utah-basedLocally deployedAccess controlledManaged end to end
The adoption gap
Businesses want AI. They do not want to lose control.
Public AI tools are useful, but they were not designed around every company’s data boundaries, identity system, or operating requirements.
Subscriptions multiply
Per-user tools accumulate across departments while access, usage, and value become difficult to manage.
Company knowledge stays fragmented
Useful context remains scattered across file shares, drives, inboxes, and business systems.
Permissions do not follow the employee
A generic chatbot cannot safely infer which financial, HR, sales, or operational data a user should see.
The Deep Conduit platform
The operating layer that makes private AI usable
Hardware and models are ingredients. Deep Conduit connects them to identity, authorized company knowledge, approved workflows, and ongoing operations.
Local inference
Run capable local and open models on NVIDIA, Apple Silicon, GPU servers, or other infrastructure selected for the workload.
Company knowledge
Retrieve current information from approved documents and systems with source citations—without retraining a model for every update.
Identity and access
Integrate SSO, roles, group membership, and department boundaries before information is retrieved.
Agents and workflows
Connect approved tools for research, analysis, reporting, proposals, and repeatable work inside controlled execution boundaries.
Simple employee experience
Employees see a straightforward interface. They do not need to manage models, embeddings, GPUs, or inference servers.
Managed operation
Benchmarking, monitoring, upgrades, evaluation, and support keep the system useful as models and business needs change.
Security before generation
The same question should not reveal the same data to everyone.
Each employee signs in with company identity. The platform applies existing permissions and retrieves only the sources that person is authorized to use.
The model does not decide what a user is allowed to see.Authorization happens before data reaches the model.
Explore the security architecture →ONE COMPANYTWO AUTHORIZED VIEWS
S
Sales employeeSales group
- CRM records
- Proposals
- Customer documentation
- Sales knowledge
Finance data blocked
F
Finance employeeFinance group
- Accounting records
- Invoices
- Margins
- Financial reports
Sales notes excluded
How it works
From requirements to reliable operation
Assess
Evaluate workflows, users, data, security requirements, and the business case.
Deploy
Install private AI infrastructure on-premises or in a controlled environment.
Connect
Integrate identity, documents, knowledge bases, and approved business systems.
Operate
Employees use a simple interface while Deep Conduit manages updates, monitoring, and optimization.
Practical use cases
Start with work your team already does
Document and contract analysisInternal knowledge searchEmail and proposal draftingEngineering and technical supportReporting and data analysisCompany-specific researchSecure departmental assistantsWorkflow automation
Ways to engage
A practical path into private AI
Begin with a focused assessment, move into a secure deployment, and keep the system current with managed operation.
Private AI Assessment
Define priority workflows, data boundaries, security requirements, architecture options, and a deployment roadmap.
Learn about assessment →Private AI Deployment
Implement infrastructure, models, identity, secure retrieval, approved tools, employee interface, and onboarding.
Explore deployment →Managed Private AI
Ongoing monitoring, model evaluation, upgrades, usage review, security maintenance, and workflow improvement.
See managed operation →Built by operators
Production experience, not presentationware.
Deep Conduit builds and operates real data systems. LandPlanner.ai combines more than 15 public data sources, document interpretation, predictive models, reporting, access controls, and production monitoring.
The same engineering discipline—measured performance, explicit permissions, observable systems, and honest limits—guides every private AI deployment.
PRODUCTION SYSTEM
Data integration15+ public sources
Knowledge layerDocument interpretation
OperationsMonitoring + audit trails
DeliveryPlain-language reports
Deep Conduit
Enterprise AI experience, built for growing businesses.
Deep Conduit is a Utah technology company led by an AI enablement and infrastructure professional with experience supporting AI adoption in a large-scale Meta environment, alongside hands-on data center, systems, and software engineering work.
Meta is not a customer, partner, sponsor, or endorser of Deep Conduit.
About Deep Conduit →Private AI pilot
Bring Private AI Into Your Business
Start with one valuable workflow, a defined group of users, and clear security boundaries.
Explore a Pilot →