Grounded by default
Every answer cites its sources. If the corpus doesn't support a claim, the system says so instead of guessing.
About
AI answers you can verify
Veritas AI exists because enterprises don't need chatbots that sound confident — they need systems that are provably grounded in their own documents.
We started Veritas AI after watching the same failure repeat across teams: a demo chatbot dazzles, ships, and then quietly invents policy details in front of customers. The fix isn't a bigger model — it's retrieval that finds the right evidence, generation that refuses to leave it, and citations that let anyone check the work. That discipline is the product.
Principles
How we build
The engineering values behind every design decision in the platform.
Composable, never coupled
Embeddings, stores, rerankers, and LLMs sit behind registries. Swapping a provider is a config change, not a rewrite.
Observable everywhere
Per-stage latency, token spend, and eval scores are built in. You cannot operate what you cannot see.
Untrusted by design
Ingested content is data, never instructions. Prompt-injection defense is an architecture decision, not a patch.
Measured, not vibe-checked
Faithfulness, relevancy, and context quality are numbers we track on live traffic — regressions surface before users notice.
Local-first, scale-ready
The same pipeline runs on a laptop with zero cloud dependencies and on a sharded GPU fleet. No divergent codepaths.
Building something that needs to be right?
We'd love to show you what grounded AI looks like on your own documents.