PocketFab integrated AI
Bring generative AI inside your business with PocketFab AI. Our self-hosted AI platform gives your team a company-managed workspace for drafting, summarizing, and exploring ideas. Plan your private AI deployment around supported language models, company-controlled servers, and your information-handling requirements.
Running at PocketFab. Further testing is underway. Contact us about demonstrations and deployment availability.
Run a supported large language model (LLM) on company-controlled hardware. Local model processing gives your organization direct control over where AI requests are handled. Decide which workflows belong in your private environment and which may use approved outside services.
Give employees a browser-based place to work with AI. Start with drafting, summarization, and everyday questions, then evaluate results against your own requirements.
Match the model, GPU capacity, memory, and storage to your workload. Test response time, concurrent users, and answer quality with representative tasks before expanding your enterprise AI deployment.
PocketFab AI is the application around your private AI environment, licensed through PocketFab ALM. The underlying language models retain their own licenses.
For law firms and businesses
Explore drafting assistance, summaries, and internal questions with approved test material. Compare the answers with your team's standards before introducing sensitive or business-critical work.
For institutional knowledge and document search, discuss retrieval-augmented generation (RAG): retrieving authorized source material to help inform an answer. An AI knowledge base, document repositories, and matter-level access controls require a defined integration scope and separate validation. They are not assumed to be included in every deployment.
Local model processing can keep prompts away from an external inference provider. Plan data residency, user access, storage, backups, logging, retention, updates, licensing connections, and optional integrations together. Enterprise AI governance should cover the full operating environment, including any data sovereignty requirements.
Private hosting does not guarantee isolation, compliance, or accurate answers. Your team remains responsible for reviewing AI output and approving how information is used.
What does native AI mean here? Bringing the AI workspace and supported model processing into your business environment. PocketFab AI focuses on private, locally hosted AI under company control. The deployment plan defines where models run, who can use them, and which connections are permitted.
How does self-hosting differ from on-premises AI? On-premises AI runs on hardware at your location. Self-hosting means your organization operates the environment, which may be on-site or on infrastructure elsewhere under its control. Discuss your required location, network boundaries, and operational responsibilities with PocketFab before choosing a deployment.
Can a private AI assistant help address shadow AI? An approved workspace gives employees a defined place for permitted tasks. Pair it with training, acceptable-use rules, and oversight of external services. Read our guide to shadow AI and confidential company information.
Does local processing mean offline or air-gapped AI? No. Licensing, updates, remote access, and integrations must be reviewed across the complete application. Disconnected operation requires explicit assessment and validation for the proposed deployment.
Plan your deployment
Tell us about your users, tasks, existing hardware, and information-handling requirements. We will discuss model selection, infrastructure sizing, pilot testing, and PocketFab application licensing. Start with a defined use case and measurable acceptance criteria.
Talk with PocketFab →