Enterprise LLM Integration
Connect private AI to the systems your business already runs on.
Cloud, on-prem, or at the edge.
Same model, same governance, same control plane — sized and operated for the environment that fits your security, latency, and cost profile.
- On-prem for full data sovereignty
- Private cloud (AWS · Azure · GCP) for elastic scale
- Edge for offline + low-latency environments
Today's enterprises don't need another SaaS subscription—they need intelligent infrastructure. At LLM.co, we deliver fully private, fine-tuned Large Language Models (LLMs) designed for enterprise-grade performance, governance, and control. Whether you're a law firm, financial institution, manufacturer, or healthcare system, we build bespoke AI stacks that integrate directly into your systems—on-premise or in your VPC—with the privacy, security, and scalability your business demands.
Streamline Your Workflow With Our AI Platform
An Enterprise LLM is not just a chatbot with a logo. It's a custom-trained language model engineered to understand your business context, operate within your compliance framework, and perform consistently at scale. Unlike public LLMs or cloud APIs, an enterprise LLM: Runs inside your infrastructure, Understands your unique data and terminology, Supports role-based access, audit trails, and strict permissions, Is compliant, controllable, and custom-built.
Data Private by Default
All data stays within your walls—no API calls, no cloud leakage, no usage tracking. We work with IT and compliance teams to ensure total data control. From inboxes and PDFs to databases and proprietary systems, our LLMs provide semantic understanding across your enterprise—fast, accurate, and secure.
Scalable, Agnostic
Deploy across departments, teams, or regions without losing consistency. Our models scale with your needs while remaining tightly governed and version-controlled. Run your LLMs on-prem, in your cloud (AWS, Azure, GCP), or in hybrid environments. We support Docker, Kubernetes, and bare metal.
Fully Custom
Build domain-specific AI agents for legal drafting, internal search, summarization, RFP generation, contract review, and more. Trained on your data, tuned for your business logic.
Serving Compliance-Heavy Industries
We service some of the most compliance-heavy industry sectors:
Internal Knowledge Management: Vector-based search across wikis, docs & Slack
Industrial Operations: SOP interpretation, field team Q&A, safety protocols
Healthcare Providers: Note summarization, diagnosis suggestion (HIPAA-ready)
Finance Departments: Report generation, compliance Q&A, data extraction
Legal Teams: Drafting, reviewing, and summarizing contracts & case law
From Proof of Concept to Full Deployment
Whether you're experimenting or rolling out org-wide, we meet you where you are:
Discovery & Use Case Mapping
Data Ingestion & Indexing
Secure Model Deployment (VPC or On-Prem)
UI/API Layer Buildout
Governance, Training, Support
Why LLM.co?
Unlike cloud-native AI providers, we don't sell your data or resell your prompts. We architect AI that belongs to you, runs in your infrastructure, and speaks your language.
Enterprise, Private LLM & AI Software Features
Email/Call/Meeting Summarization: LLM.co enables secure, AI-powered summarization and semantic search across emails, calls, and meeting transcripts—delivering actionable insights without exposing sensitive communications to public AI tools. Deployed on-prem or in your VPC, our platform helps teams extract key takeaways, action items, and context across conversations, all with full traceability and compliance.
Security-first AI Agents: LLM.co delivers private, secure AI agents designed to operate entirely within your infrastructure—on-premise or in a VPC—without exposing sensitive data to public APIs. Each agent is domain-tuned, role-restricted, and fully auditable, enabling safe automation of high-trust tasks in finance, healthcare, law, government, and enterprise IT.
Internal Search: LLM.co delivers private, AI-powered internal search across your documents, emails, knowledge bases, and databases—fully deployed on-premise or in your virtual private cloud. With natural language queries, semantic search, and retrieval-augmented answers grounded in your own data, your team can instantly access critical knowledge without compromising security, compliance, or access control.
Multi-document Q&A: LLM.co enables private, AI-powered question answering across thousands of internal documents—delivering grounded, cited responses from your own data sources. Whether you're working with contracts, research, policies, or technical docs, our system gives you accurate, secure answers in seconds, with zero exposure to third-party AI services.
Custom Chatbots: LLM.co enables fully private, domain-specific AI chatbots trained on your internal documents, support data, and brand voice—deployed securely on-premise or in your VPC. Whether for internal teams or customer-facing portals, our chatbots deliver accurate, on-brand responses using retrieval-augmented generation, role-based access, and full control over tone, behavior, and data exposure.
Offline AI Agents: LLM.co's Offline AI Agents bring the power of secure, domain-tuned language models to fully air-gapped environments—no internet, no cloud, and no data leakage. Designed for defense, healthcare, finance, and other highly regulated sectors, these agents run autonomously on local hardware, enabling intelligent document analysis and task automation entirely within your infrastructure.
Knowledge Base Assistants: LLM.co's Knowledge Base Assistants turn your internal documentation—wikis, SOPs, PDFs, and more—into secure, AI-powered tools your team can query in real time. Deployed privately and trained on your own data, these assistants provide accurate, contextual answers with full source traceability, helping teams work faster without sacrificing compliance or control.
Contract Review: LLM.co delivers private, AI-powered contract review tools that help legal, procurement, and deal teams analyze, summarize, and compare contracts at scale—entirely within your infrastructure. With clause-level extraction, risk flagging, and retrieval-augmented summaries, our platform accelerates legal workflows without compromising data security, compliance, or precision.
Data Ingestion from Your Favorite Applications
Ingest your data from nearly any private or public source, keep it HIPPA and SOC compliant through the LLM ingestion and RAG process.
Pre-Built Connectors for the Systems You Already Run
Enterprise LLM integration starts where your data already lives. LLM.co ships secure connectors for CRMs (Salesforce), collaboration platforms (Microsoft SharePoint, Slack, Microsoft Teams), ITSM systems (ServiceNow), relational and vector databases, and enterprise data warehouses such as Snowflake. Each connector authenticates over encrypted channels, respects existing permission boundaries, and writes nothing back to public infrastructure. Rather than building brittle point-to-point integrations, we expose a unified REST API layer so internal applications—ERP, ticketing, portals, or custom line-of-business tools—can query your private LLM through a single, auditable endpoint.
For document-heavy workflows, connectors reach into SharePoint libraries, OneDrive, Confluence wikis, and shared network drives to feed a continuously updated RAG index. The result is an internal search and knowledge-base assistant that answers questions against live enterprise content—without routing any document or prompt through a third-party cloud service.
Integration Architecture: APIs, SSO, and Data Pipelines
Our integration stack is built around an OpenAI-compatible REST API gateway deployed entirely inside your VPC or on-premises environment. Incoming requests pass through an identity layer that enforces SAML 2.0 or OIDC single sign-on, maps users to role-based access control (RBAC) groups, and applies prompt-level filtering before any token reaches the model. This means a finance analyst sees only finance-approved data sources, while a legal team member operates within a fully separate, permissioned context—same model, different data boundaries.
Data pipelines follow a retrieve-then-generate pattern: documents are ingested, chunked, and indexed into a private vector store; at inference time, the API retrieves relevant passages and injects them as grounded context. All pipeline stages—ingestion, embedding, retrieval, generation, and response logging—run inside your infrastructure. SCIM provisioning integrates with your identity provider to keep access current as staff join, change roles, or leave. Audit logs are immutable, exportable, and structured for SIEM ingestion. Learn more about on-prem deployment and hybrid architecture options.
Security and Compliance by Design
Enterprise LLM integration introduces new attack surfaces if not architected carefully. LLM.co's deployment model eliminates the most common risk vector—external API calls—by keeping all inference local. Data in transit is encrypted with TLS 1.2+; data at rest uses AES-256 encryption managed by your own key management service, not ours. We work directly with your IT security, legal, and compliance teams during scoping to map controls to relevant frameworks: SOC 2, HIPAA, ISO 27001, and FedRAMP-adjacent environments.
Role-based access controls govern which users can invoke which capabilities—query a knowledge base, trigger an automation, or run an agentic workflow. Every LLM action is logged with user identity, timestamp, retrieved sources, and response hash, producing an auditable trail that satisfies both internal governance requirements and external audit reviews. No prompt, document, or output ever leaves your defined security perimeter.
Common questions
01Which enterprise systems can LLM.co integrate with?
LLM.co provides connectors for a broad range of enterprise platforms including Salesforce, Microsoft SharePoint, ServiceNow, Slack, Microsoft Teams, Snowflake, and standard relational databases. Integration is handled over a secure REST API layer deployed inside your VPC or on-premises environment, so data never transits a public cloud endpoint. Additional connectors can be built to fit proprietary or legacy line-of-business systems.
02How does SSO and identity management work with a private LLM deployment?
LLM.co's API gateway enforces SAML 2.0 or OIDC single sign-on, connecting directly to your existing identity provider—whether that is Okta, Azure AD, or an on-premises LDAP directory. SCIM provisioning keeps user roles synchronized automatically, and RBAC policies control which data sources and model capabilities each user group can access. No separate credential store is created outside your perimeter.
03Does the LLM have access to all our data, or can access be scoped by department?
Access is scoped at both the data-source and role level. Each user or group is mapped to a specific set of permitted data sources—documents, databases, or connectors—and the model only retrieves context from within that permitted set at inference time. A legal team member cannot surface finance documents, and vice versa, even though both may query the same underlying model instance.
04What does the integration process look like from kickoff to production?
Engagements follow a structured sequence: discovery and use-case mapping, connector configuration and data ingestion, secure model deployment into your VPC or on-premises hardware, API and UI layer buildout, and governance configuration including RBAC, audit logging, and SSO. Most production deployments move from signed agreement to a working internal pilot within weeks, not quarters. Ongoing support and model retraining are available post-launch.
05Can the integration support both cloud-hosted and fully air-gapped environments?
Yes. LLM.co supports three deployment postures: fully on-premises (including air-gapped environments with no internet egress), private cloud VPC deployment on AWS, Azure, or GCP, and hybrid configurations where some workloads run on-prem and others in a private cloud segment. The same connector framework, RBAC model, and audit pipeline apply across all three, so compliance posture is consistent regardless of where compute runs.
Private AI On Your Terms
Tell us your use case and constraints — on-prem, cloud, or edge — and we'll map a compliant deployment within one business day.
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