LLM Deployment for Business
Large language models — Claude, ChatGPT, Gemini — are genuinely powerful. They can also be genuinely problematic if deployed without a clear framework. Employees using personal AI accounts with company data, inconsistent outputs, no audit trail, no governance: these are real risks that forward-thinking businesses need to manage. Forward helps you deploy LLMs in your business correctly — with the right model selection, access controls, data boundaries, and integration into actual workflows.
The Deployment Decision
Not every LLM is right for every use case. The differences between Claude, ChatGPT, Gemini, and purpose-built models matter:
- Context window size: how much text the model can process at once — critical for document-heavy workflows
- Instruction following: how reliably the model follows complex, multi-step instructions
- Language support: Hebrew and other non-English languages perform differently across models
- Data handling: what happens to your data when you send it to the model’s API
- Cost structure: token pricing varies significantly, and adds up fast at scale
We help you evaluate these factors against your actual use cases and make the right selection.
What Correct Deployment Looks Like
Access management: Who can use which models, for which purposes, with what data. Not everyone needs the same access level.
Data boundaries: What information can go into the model, and what can’t. Especially important for businesses in regulated industries or with sensitive client information.
Prompt governance: Standardized prompts for common use cases ensure consistent, reliable outputs. Ad-hoc prompting by untrained employees produces inconsistent results.
Integration: LLMs deliver the most value when integrated into existing workflows — connected to your CRM, documents, or communication tools — not as standalone chat interfaces.
Audit and monitoring: Logs of what was sent, what was received, and by whom. Required for compliance in many sectors.
How We Help
We handle the technical deployment, the governance framework, the employee training, and the ongoing monitoring. You get a working system with the controls in place — not a raw API key and good luck.