Welcome to VeldrixAI
VeldrixAI is the runtime trust infrastructure layer for production AI systems — it evaluates every model output, enforces your governance policy, and writes a tamper-evident audit trail.
What is VeldrixAI?
VeldrixAI sits between your AI application and your users. Every time your system produces a model response, VeldrixAI evaluates that response across five independent trust dimensions, aggregates the results against your policy, decides on an enforcement action, and records the decision in an immutable audit log.
Think of it as the control plane for AI behaviour: your LLM decides what to say, and VeldrixAI decides whether that output is allowed to ship — with the evidence to prove it later.
Why it matters
Foundation models are non-deterministic. The same prompt can return a safe answer today and a harmful, hallucinated, or non-compliant one tomorrow. For consumer apps that is a reputation risk; for regulated industries — healthcare, finance, legal, government — it is a compliance liability.
VeldrixAI gives you three things teams need to run AI in production with confidence:
Real-time guardrails
Catch unsafe, hallucinated, biased, or PII-leaking output before it reaches a user.
Deterministic policy
Encode your risk tolerance once. Every evaluation applies it identically and reproducibly.
Provable accountability
A cryptographically chained audit trail your compliance and security teams will accept.
How it works
A single evaluation flows through the Trust Engine in four stages:
Intercept. You send the prompt + the model response to VeldrixAI (inline, or in the background so it never slows your app).
Evaluate. Five pillars run in parallel against the content, each returning a 0–1 score and any flags.
Decide. The Policy Engine aggregates pillar scores with your weights, compares against your thresholds, and resolves a verdict: ALLOW, WARN, REVIEW, or BLOCK.
Record. The full decision is written to your append-only audit trail and surfaced in the dashboard.
The five pillars
Safety & Toxicity
Harmful, violent, harassing, or self-harm-inducing content.
Hallucination Detection
Fabricated facts, false citations, invented statistics.
Bias & Fairness
Discriminatory framing and demographic stereotyping.
Prompt Security
Injection attacks, jailbreaks, and adversarial patterns.
Compliance & PII
Regulated data categories and personal-information disclosure.
Next steps
Follow the Quickstart to run your first evaluation in under five minutes.
Read Core Concepts to understand trust scores, verdicts, pillars, and policies.
Integrate via the Python SDK or the REST API.