LLM Authority
Access control for agents and AI models
LLM Authority is an access-control layer between your agents and AI model providers, and much more: four pillars built as one system, so every request is checked against the agent, the person behind it and what it's sending.
At a glance
What's in LLM Authority
- Why it's differentAgent, person, model, prompt and budget, on every requestAnatomy of one request
- Agent visibilityEvery agent calling a model, and the person behind itModel activity · Audit trail
- Data protectionCustomer details removed before a prompt leavesRedact or block · Rules by team
- Models & budgetsApproved models per team, spend stopped at the limitModels by team · Budgets · Model providers
- Prompt controlRisky prompts caught before the model actsClassification · Injection detection · Alerts
Why LLM Authority
Every model request is checked before it leaves
Let agents call models directly and nothing stands between a prompt and the provider. LLM Authority checks the person, the agent, the model, the prompt and the budget on every request.
- One checkpoint between your AI tools and the models
- Checked in real time, on every request
- Your people keep the AI tools they like
- Matched
Person
Sales rep
A verified person from your IdP, group Sales
- Approved
Agent
Sales agent
Its own identity, tied to that person
- Approved
Model
claude-sonnetSales may use Sonnet only
- 3 redactions
Prompt contents
A customer name, phone and account
Found and removed before the prompt leaves
- Within budget
Budget
$1,880 of $2,000 this month
Sales at 94%, requests stop at $2,000
- Allowed with redaction
Decision
Sent to the model, with placeholders
Logged with the agent, the person and the model
Pillar 1 · Agent visibility
Know which agents call AI models, and for whom
Most teams can't answer this today. Each prompt and response is logged with the agent, the person behind it and the model it reached.
- Each agent gets its own identity, tied to a verified person from your IdP
- A full audit trail you can search or send to your SIEM
- Cut off one agent without stopping the person who started it
Pillar 2 · Data protection
Keep customer data out of ChatGPT, Claude and Gemini
People paste customer names, phone numbers and account details into prompts every day. LLM Authority finds them and removes them before the prompt leaves your company.
- Redact or blockStrip the details and let the work go on, or stop the prompt when it shouldn't leave at all.
- Rules by teamFinance and support can have stricter rules than engineering.
- Checks on your own modelContent checks can run on a model endpoint you already approve.
What the person typed
Write a follow-up email to Dana Reyes at (415) 555-0142 about the late payment on account 4410-2283-9917.
What the model receives
Write a follow-up email to [CUSTOMER] at [PHONE] about the late payment on account [ACCOUNT].
Pillar 3 · Models & budgets
Pick each team's models, and stop spend at the budget
Nobody needs the most expensive model to build a spreadsheet. Set models and budgets by team or by person, using the groups you already have.
- Spend shown by team, person and model, against what you actually pay
- An agent burning through tokens is cut off automatically
Model providers
- OpenAI
- Anthropic
- Google Gemini
- Azure OpenAI
- Amazon Bedrock
Each request an agent sends to a model from these providers is checked in real time.
Pillar 4 · Prompt control
Catch risky prompts before the model acts on them
For teams that want to go further, LLM Authority reads the intent of each prompt as well as the data in it.
Prompt classification
Sort prompts by what they're trying to do, and apply rules to each kind.
Injection detection
Flag instructions hidden in documents or tickets that try to steer the model.
Unusual activity alerts
Get told when someone starts using a new model or spend jumps overnight.
Part of Agent Authority
One authority for every path an agent takes
LLM Authority is one of three enforcement paths in Agent Authority, alongside MCP Authority and Endpoint Authority.
Where AI runs
Agent Authority
One policy on every path
What it reaches
Employees and desktop agents
Endpoint Authority
Discover AI apps, block unsanctioned tools
Local files and shadow AI
Agents calling tools over MCP
MCP Authority
Authorize every tool call, scoped to the task
Enterprise apps and data
Prompts from users and agents
LLM Authority
Redact sensitive data, stop prompt injection
Model providers
LLM Authority FAQ
What is LLM Authority?
LLM Authority is the access-control layer in Agent Authority between your agents and the AI model providers they call. Each request an agent sends to a model is checked in real time against who the agent is, the person behind it and what it's trying to send. It brings four pillars together as one system: agent visibility, data protection, models and budgets, and prompt control.
Which AI model providers does LLM Authority cover?
LLM Authority covers models from OpenAI, Anthropic, Google Gemini, Azure OpenAI and Amazon Bedrock.
Can we see which agents are calling AI models?
Yes. Each agent gets its own identity, tied to a verified person from your IdP, and each prompt and response is logged with the agent, the person behind it and the model it reached. You can search the audit trail or send it to your SIEM, an agent that isn't on your approved list is flagged for review, and you can cut off one agent without stopping the person who started it.
How does LLM Authority keep customer data out of prompts?
It finds customer names, phone numbers and account details in a prompt and removes them before the prompt leaves your company, so the model receives the same request with placeholders. You can strip the details and let the work go on, or stop the prompt when it shouldn't leave at all. Finance and support can have stricter rules than engineering, and content checks can run on a model endpoint you already approve.
Can we control which models each team uses and what it spends?
Yes. Set models and budgets by team or by person, using the groups you already have. Spend is shown by team, person and model, against what you actually pay, requests stop when a budget runs out, and an agent burning through tokens is cut off automatically.
Does LLM Authority catch prompt injection?
Yes. Injection detection flags instructions hidden in documents or tickets that try to steer the model. Prompt classification sorts prompts by what they're trying to do so you can apply rules to each kind, and unusual activity alerts tell you when someone starts using a new model or spend jumps overnight.
Do people have to change the AI tools they use?
No. Your people keep the AI tools they like, with no agent rewrite and no SDK. You add one checkpoint between those tools and the models by pointing each tool or agent at one endpoint, one line per tool.
Let agents use AI models on your terms
14-day free trial. Your own Agent Authority tenant. Read the setup docs.
Start free trial