New interactive tool helps enterprises estimate the cost of private AI deployments across infrastructure, security, and deployment models
-- LLM.co today announced the release of its Private LLM Pricing Calculator, an interactive web-based tool designed to help businesses estimate the real-world costs of deploying private large language models. The calculator enables organizations to model deployment scenarios across multiple industries—including legal, finance, healthcare, and enterprise SaaS—while accounting for infrastructure, hosting, security, and integration requirements.
As demand for private and secure AI environments accelerates, many organizations struggle to understand the financial implications of moving from public AI tools to private deployments. LLM.co developed the calculator to provide a structured, transparent way to evaluate tradeoffs between deployment architectures such as self-hosted models, retrieval-augmented generation (RAG) systems, hybrid cloud environments, and fully managed private AI platforms.
The calculator walks users through a structured decision tree, allowing them to specify:
- Industry-specific compliance and data requirements
- Model size and performance expectations
- Hosting and infrastructure preferences
- Integration and API needs
- Security and governance controls
- Expected user volume and query loads
Based on these inputs, the system produces estimated monthly and annual cost ranges, along with recommended architectural approaches.
“Organizations are moving quickly toward private AI, but most buyers still lack a clear framework for understanding cost drivers,” said Timothy Carter, CRO of LLM.co. “This calculator gives technical leaders and executives a practical way to model scenarios before they commit capital or begin implementation.”
The release comes at a time when enterprises are increasingly prioritizing data privacy, intellectual property protection, and regulatory compliance in AI deployments. Industries such as legal services, financial institutions, and healthcare providers are among the fastest adopters of private LLM infrastructure, driven by the need to keep sensitive information within controlled environments.
In addition to cost estimates, the tool provides guidance on architectural decisions, helping users understand when to consider:
- Fully self-hosted GPU infrastructure
- Private cloud deployments
- Hybrid RAG systems using vector databases
- Secure API-based model hosting
- Fine-tuning versus prompt engineering strategies
“Many organizations underestimate the operational and infrastructure components of private AI,” Nead added. “We built this tool to surface those variables early so teams can plan realistically rather than rely on rough assumptions.”
The Private LLM Pricing Calculator is available now on the LLM.co website and is designed for CIOs, CTOs, legal technology teams, AI engineers, and private equity-backed portfolio companies evaluating internal AI deployments.
About LLM.co
LLM.co is a consulting and engineering firm focused on private large language model deployment, secure AI infrastructure, and enterprise AI integration. Incubated from a software development services company, the firm helps organizations design, build, and operate custom AI environments tailored to their data, security, and performance requirements. Services include private LLM architecture, retrieval-augmented generation systems, model fine-tuning, and enterprise AI workflow integration.
Contact Info:
Name: Samuel Edwards
Email: Send Email
Organization: Link Build
Website: https://link.build
Release ID: 89182949
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