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DoopalAI

DoopalAI is a zero-trust AI gateway for enterprise LLM access. It sits between your apps and models to block sensitive data leaks, enforce policy-as-code governance, and track usage costs—so teams can run AI safely and efficiently.
Rating:
5
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Features of DoopalAI

Gateway layer between apps and models that enforces unified pre- and post-request security & governance.
Detects and redacts PII, PHI, secrets, and proprietary code to cut exposure risk.
Combines rule-based and semantic detection across text, JSON, code blocks, and streaming outputs.
Policy-as-Code engine lets you set rules by user, model, content type, or projected token cost.
Actions include allow, transform, or block so you can apply differentiated controls per scenario.
Dry-run, canary, and phased roll-outs let teams validate new policies without downtime.
Multi-tenant isolation plus real-time API overrides fit complex org and environment needs.
Logs every request, policy decision, and response—searchable and replayable for audits.
Cost attribution by model, project, and policy action with anomaly alerts and budget caps.

Use Cases of DoopalAI

Centralize auth, routing, and security when connecting multiple LLMs across the company.
Redact prompts and filter outputs in customer-support, healthcare, or finance workflows that handle sensitive data.
Security teams preview impact of new blocking rules with dry-run and canary releases.
Compliance and internal audit teams trace, replay, and export evidence from request & decision logs.
Platform owners allocate LLM budget by department or project, watch for spikes, and cap spend.
Isolate business units and apply fine-grained policies when several teams share the same AI backends.
Stop prompt injection and unauthorized calls with unified guardrails at the gateway layer.

FAQ about DoopalAI

QWhat is DoopalAI?

DoopalAI is a zero-trust AI gateway that sits between your applications and large language models to deliver security, policy governance, audit trails, and cost control.

QWhich enterprise problems does DoopalAI solve?

It reduces the risk of sensitive data leaks, unifies model-access policies, improves auditability, and helps control token spend.

QWhat types of sensitive data can DoopalAI protect?

It identifies and redacts PII, PHI, secrets, and proprietary code in text, JSON, code blocks, and streaming outputs.

QHow is policy governance configured?

Use Policy-as-Code to define rules by user, model, content category, security label, or estimated token cost, then allow, transform, or block requests.

QDoes DoopalAI support audit and replay?

Yes—every request, policy decision, and model response is logged, searchable, and replayable for troubleshooting and compliance reviews.

QHow does DoopalAI help control LLM costs?

It attributes spend by model, project, and policy action and sends anomaly alerts or enforces budget caps to support FinOps practices.

QWhich teams should use DoopalAI?

Security, platform engineering, compliance, and AI product teams that need centralized governance over LLM usage.

QIs there a free tier or published pricing?

No pricing details are provided here; check the official website or contact sales for the latest plans.