We Don't Guess. We Cite.
The fear of AI hallucinations is real — and on a job site, a confidently wrong answer costs more than a wrong search result. That's why every SpaceCapture answer is built from your own documents: if it's not in your manual, our AI won't say it.
Last updated: September 2026
Why a Confident Wrong Answer Is Worse Than No Answer
General-purpose chatbots are trained to be helpful, so when they don't know something, they fill the gap with something plausible. Ask one for a flange torque spec and it will happily give you a number — round, specific, and invented.
On paper that's an annoyance. In the field it's a hazard: an inspector who trusts a made-up spec can sign off on a bolted joint that was never tightened correctly, and a compliance answer that sounds right but cites nothing can't be defended in an audit.
SpaceCapture is built the other way around. The AI is only allowed to answer from your documents, cite what it used, and admit when the answer isn't there. Useful when it knows. Silent when it doesn't.
Upload Your Truth
You upload your SOPs, ISO standards, and equipment manuals. We index them into a private search store unique to your workspace — this becomes the only source the AI is allowed to answer from.
The "Silence" Protocol
Standard LLMs try to be helpful by making things up. Ours is built to say "I don't know" or "reference needed" when your documents don't cover the question — because an honest gap is safer than a confident guess.
Your Data Standards, Enforced.
See how our Citation Engine links every AI insight back to a specific page in your PDF manual.
Request Compliance DemoGrounded by VeritasGraph
The citation engine above runs on the VeritasGraph open-source GraphRAG framework — the same attribution layer behind search and AI answers across SpaceCapture. It links every claim to its source document or capture and shows the reasoning path, so hallucination-free isn't a promise, it's checkable.
See how SpaceCapture verifies AI answers →Hallucination-Free AI: Questions, Answered
How grounding, citations, and the Silence Protocol keep AI answers honest.
What is an AI hallucination?
An AI hallucination is a confident answer that isn't true — a torque spec nobody wrote down, a clause that doesn't exist in your contract. On a real inspection, a made-up answer can pass a defect or fail equipment that's perfectly fine, so guessing isn't a small failure mode.
How does SpaceCapture stop the AI from making things up?
Grounding. You upload your SOPs, ISO standards, and equipment manuals, and every answer is built from those documents only. The AI quotes the passage it used and attaches the file and page as a citation, so you can check the answer in one click.
What does the AI say when it doesn't know the answer?
Nothing invented. When your documents don't cover a question, SpaceCapture says so and flags the missing reference instead of filling the gap with a plausible-sounding guess. That's the Silence Protocol: an honest "reference needed" beats a confident wrong answer every time.
Can I see where an answer came from?
Yes. Every answer shows its source — the exact file and page, like Manual_V164_v3.pdf page 42 — plus a confidence score. Click the citation and you're reading the original passage yourself, so verification never depends on trusting the model.
Does SpaceCapture train public AI models on my documents?
No. Your documents are indexed into a private, single-tenant store that only your workspace can query. They answer your questions, never train shared or public models — and on-premise deployments keep everything inside infrastructure you already control.
How does VeritasGraph relate to hallucination-free answers?
VeritasGraph is the open-source grounding layer behind these citations. It connects your documents and captures into a knowledge graph, tracks every claim back to its source, and exposes the reasoning path — the same mechanism behind source attribution across SpaceCapture.
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