I built SiviGen because I got tired of a specific kind of dishonesty.
Paste a job description into most “AI CV” tools and they’ll cheerfully add skills you’ve never touched, inflate a job title, or invent a metric that reads well. It looks great in the editor. Then you sit in the interview, someone asks you to walk through the thing you supposedly did, and the whole story falls apart.
That’s the problem SiviGen refuses to have. The entire product is built around one promise: maximise relevance to the job without inventing anything. Not “minimise” fabrication. Not “usually” truthful. Zero invented facts, by design.
Here’s how that actually works under the hood.
Your CV becomes a fact graph
When you upload your CV, SiviGen doesn’t just keep the raw text around to feed back to a model later. It parses your CV once into a structured profile, then enriches that into what we call a fact graph: every role, every bullet point, every skill becomes an atomic, individually-addressable fact.
Think of it as breaking your career into its smallest true statements. “Led a team of five engineers.” “Shipped a payments integration.” “Used PostgreSQL in production.” Each of these is a node the rest of the system can point at. If you’re staring at something you did and can’t find the words for it yet, that’s exactly the gap a guided interview to turn what you did into an evidence-backed bullet is built to close.
This matters because it changes the question the AI is allowed to ask. It’s no longer “what would make this candidate look good for this job?” — a question that invites invention. It’s “which of these facts, that we already know are true, are most relevant to this job, and how should we phrase them?”
Tailoring is selection and rephrasing, never creation
When you paste a job description, SiviGen reads it and builds a match plan — a mapping between what the job asks for and what your fact graph actually contains. Then it selects and rewrites.
The keyword there is rewrites, not writes. Rephrasing “Used PostgreSQL in production” as “Operated production PostgreSQL databases supporting core services” is honest work — same fact, sharper framing, aligned to a role that cares about databases. Adding “Expert in Kafka and distributed streaming” when your CV never mentioned Kafka is not, and the pipeline is structured so it simply can’t do that quietly.
Every rewritten line has to trace back to a fact in the graph. If it can’t, it doesn’t belong on the tailored CV.
A separate pass audits every claim
Selection and rephrasing happen in one part of the pipeline. Then a completely separate step does something most tools never bother with: it reads the draft it just produced and extracts every claim from it, as if it were an adversarial reviewer seeing the CV for the first time. Each claim is checked against your fact graph and labelled — supported, unsupported, or contradicted — and the scores that follow are computed from those labels in ordinary TypeScript rather than guessed by a model.
That separation is the whole design. The part of the system that writes is not the part that judges, and it is not the part that scores either, so the honesty guarantee isn’t something the writer can talk itself out of.
You can run the same check on a single bullet yourself — paste one in and see whether you could defend the claim in an interview before it ever reaches a real CV. What each verdict actually means, how the gating behaves, and how to run the audit by hand on a CV you already have are covered properly in the truthfulness audit, explained.
Why “veridical” is the whole point
There’s a version of this product that would be easier to build and, honestly, flashier in a demo: just let the model write whatever makes the candidate look strongest. It would impress people for about as long as it takes to reach a real interview.
SiviGen exists for the opposite reason. A CV you can’t defend in the room isn’t an asset — it’s a liability with good production values. The goal here is the strongest possible version of your real story: every line true, every claim traceable, and a relevance score you earned rather than faked.
That’s a narrower path than “make something up that fits.” It’s also the only one worth walking.
If that’s the kind of CV you want to send, give it a try.