Obiguard gives security teams the controls, visibility, and evidence they need to govern AI the same way they govern every other critical system in their stack.
A live dashboard shows threats blocked, violations by severity, token usage, and cost — per agent, per project, across your entire org.
Policy decisions happen synchronously. A blocked prompt never reaches the model. A redacted response never reaches the user. No async lag. Streamed responses are checked after delivery and recorded.
Eight model-backed and five rule-based guards cover prompt injection and jailbreaks, PII and sensitive data, NSFW and toxic content, profanity, ban lists, and competitor mentions — plus keyword, regex, and LLM-judge criteria you write yourself.
Export request records, decisions, and the Audit Log to CSV or JSON for your SIEM or GRC pipeline.
Run Project Moonshot benchmarks and attack modules against a registered agent — jailbreak resistance, privacy leakage, safety and bias — and get a graded result per recipe before the agent ships.
A nightly job samples yesterday’s traces and scores them for toxicity, bias, misinformation, and privacy leakage — catching the drift a static policy cannot describe in advance. Fully asynchronous, never on the request path.
A 20-minute scoping call is enough to design your policy model and estimate deployment time. Most security teams are enforcing policy in production within two weeks.
