How do we know what AI is being used?
AI Inventory tracks every app, agent, model, provider, and tool. Periodic snapshots diff against the live list. A new, unregistered asset appears as a shadow-AI signal before it becomes a risk.
Solutions · Enterprise
How do we stop banning AI?
You stop banning it by giving people a sanctioned tool that is better than the workaround. One console, every model, your policies running before each call, and spend tracked to the team and the decision that spent it.
Runs inside your AWS, GCP or Kubernetes install.
Last reviewed
Illustrative. No customer data.
The difference
Their way, and ours.
Their wayRaidu
Ban the tools and wait for the workarounds.A sanctioned console people choose because it works better.
One policy per tool, managed separately.One policy stack, applied to every call from every surface.
Find out what was spent at month end.Spend tracked to the team and the decision, with budgets and alerts.
Shadow AI disappears when the approved tool is faster, covers more models, and writes a tamper-evident record that keeps the security team satisfied.
Source: Tower AI Console and AI Inventory
What the CISO and CFO ask
Answered with what runs in the system.
Can every team run under the same policy stack?
Yes. Every call from every user, app, and agent goes through the same intercept path. 61 guardrail policies across 36 detection services run on the full prompt before the model is called. One configuration covers the whole estate.
How do we track what each team is spending?
AI FinOps gives spend by team, by model, and by decision. Budgets can be set per team, with alerts to the owner, and the spend is logged like any other decision.
Raidu capabilities
What changes when Raidu runs.
AI Console
60+ providers and 467 models. Your policies run on every call.
Read more ›AI Firewall
61 guardrail policies across 36 detection services. Every prompt checked before the model is called. Jailbreaks, data loss, and injection blocked.
Read more ›AI FinOps
Spend by team, by model, by decision, with budgets and alerts.
Read more ›The product
See the screens.
Product windows from the films, with sample data. No customer data.
The record
The spend decision, on the record.
Every call that crosses a budget threshold raises an alert. The spend is a tamper-evident entry, chained to the record before it.
- Team
- Platform engineering
- Budget remaining
- $0.00
- Verdict
- Budget alert
- Personal data
- Replaced with placeholders
- Proof
- Tamper-evident, on record
sha256 4351e90049f4fb73bcc280496903dc45…
recomputed in your browser
published with the record4351e90049f4fb73bcc28049…
Hash matches
The call path
Where every call is checked.
- InterceptEvery SDK, console and agent call
- ResolveWho, which team, which model
- InspectPolicy checks on the full prompt
- DecideAllow, refuse, or redact before the model is called
- ProveTamper-evident, write-once record of the decision
Also covered
- Shadow AI detection
- One policy stack
- Team budgets
- 467 models
- Write-once audit log
Common questions
Answered straight.
What is shadow AI and how does Raidu detect it?
Shadow AI is AI tooling used without IT or security awareness: consumer chat apps, personal API keys, unapproved plugins. AI Inventory takes periodic snapshots and diffs them against the registered list. A new unregistered model, app, or agent appears as a signal.
Can we give teams different policy sets?
Yes. Policies can be scoped by team, model, or data type. The firewall runs the relevant set on every call before the model is opened.
What happens when a team's AI budget runs out?
The budget owner is alerted as spend nears the budget threshold, and every call through Raidu is logged and on record like any other decision.
Can Raidu cover coding agents and automated pipelines, not just human users?
Yes. Every call, whether from a person in the console, an app using the SDK, or an automated agent, goes through the same intercept path.
Where does audit data live?
Inside your own cloud install.