Deploy analytics agents that cannot hallucinate.
Selfr is the first analytics agent powered by a new non-autoregressive architecture (not LLMs) that cannot hallucinate by design. It delivers factual answers that never need second-guessing.
THE PROBLEM
You can’t trust LLMs for analytics.
Hallucinations is in their DNA.
LLMs are designed to guess the next token – not give factual answers. They are prone to hallucinations and often deceive users by convincingly outputing wrong answers.
LLMs will always hallucinate.
Even with semantic layers and RAG.
Hallucinations stem from autoregression in LLMs: it's impossible to make them factual. Using a semantic layer, RAG, fine-tuning, or any trick can't fix this.
Would you deploy an AI that randomly delivers misleading information?
Deploying hallucination-prone AI technology to your customers or internal stakeholders can cost you a lot.
Legal risk
False or misleading outputs can expose your organization to lawsuits or regulatory penalties – especially in highly regulated industries.
Financial risk
Hallucinated answers, presented with confidence, can cause multi-million-dollar decision-making errors and threaten market position.
Reputation risk
When false information is presented as fact, it undermines customer trust, damages brand credibility, and can quickly escalate into public backlash.
INTRODUCING
ZH-1: The first AI model that cannot hallucinate. By design.
We designed a breakthrough model architecture that cleverly takes advantage of the structured nature of data analytics to mathematically guarantee zero hallucination.
Non autoregressive
Answers are generated in one pass through a highly parallelized process – not token by token like LLMs – thus eliminating hallucinations.
Not a black box
Unlike LLMs, ZH-1 is transparent, with every answer traceable and auditable by design. It never operates as a black box.
100% controllable
You can control and set up hard constraints for the generated output that are implemented 100% deterministically.
Deliver trusted answers.
Every. Single. Time.
Powered by our proprietary ZH-1 architecture, Selfr offers the first AI analytics solution to meet the trust and transparency requirement for large scale deployments.
CONSISTENT
Does what it says.
Says what it does.
ZH-1 explicitly states how it understands the user's question, and generates queries and answers that are – by construction – always consistent with that understanding.
CAUTIOUS
Only answers when it's sure.
Zero made-up answers.
ZH-1's unique architecture prevents it from making up answers when the source data is missing or incomplete, or when the question is too complex for it to handle.
STABLE
Ask the same questions.
Get the same answers.
Unlike LLMs, ZH-1 is architected for stability and factual accuracy: identical questions invariably yield identical answers, no matter how many times they’re asked.
The only AI you won't have to second-guess.
If you're building AI features for a truly autonomous use case – where you can't have an expert in the loop to verify queries – Selfr delivers answers your users can trust out of the box.