Use case: Enterprise LLM Access
Goal
Allow enterprise staff to improve productivity with managed access to LLM models and agents whilst managing costs, privacy, confidential information, and brand/legal compliance.
How
Create an enterprise link that allows your staff to securely login and use LLM models in a compliant way. You can control how PII and confidential information is blocked or substituted. Your staff use this chat interface rather than OpenAI or Anthropic, or Google. You can provide specific internal Agents to share and manage enterprise wide information: Internal IT Helpdesk, Product Information, Policies.
Benefit from LLMs without the worry...
Get started...
First, share the URL to login: Accessing the enterprise Chat interface is by a unique URL. Anyone from your designated email domain can securely login.
Then, your staff chat: The chat interface is just like the vendor chat interfaces with saved conversations and all the features you expect. IN ADDITION you can make internal agents available for specific purposes: Product Support Knowledge Base, Expense Reporting Policy, Customer Research Agent, whatever you need to make internal staff more productive
Some features...

Restrict Confidential and Sensitive Information
Personal identifiable information can be blocked and redacted before being sent to any LLM vendor. You remain in control of what data gets redacted, blocked or replaced based on state of the art machine learning models.

Manage Brand and Policy
Brand and policy guidelines are injected as system instructions automatically for EVERY request. This means that your enterprise voice for any generated material will be consistent and safe.

Full call log and auditing
Validate the safe use of LLM within your enterprise with a full call log, including those that have failed the safety checks. See how LLMs are being used and fine tune what models get used for what prompts to maximize quality while minimizing cost

Smart Routing (optimize speed and cost)
Reduce costs by using our smart model routing. We analyze incoming prompts and route them to different service groups. For example, simple text summarization goes to default models, whilst complex code generation or reasoning prompts get routed to the highest performance models. Typically this extends your LLM budget by 60-80% under typical use.

Token quotas and reporting
Allocate tokens on a user or department basis, controlling costs. This avoids costly surprises at the end of each month, keeping LLM usage within the budget you specify (remember, we route to lower cost models where necessary, making your budget go 60-80% further)

Eliminate Toxic and Unsafe Prompts
Toxic or unsafe prompts are blocked. You get alerted and your staff get protected from Insulting language, hate speech, harassment or abuse, profanity, violence or threat, sexual explicit or graphic prompts. This avoids unwanted surprises in any LLM responses. This is in addition to the policy and other guardrails that vendors also employ.