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AI is easy to demo. Production is the hard part.
It needs:
· Integration with your systems
· Security that passes review
· Governance where errors carry real cost
· Someone accountable once it is live
That is where OrNsoft works.
Bring us the problem, not the specification.
A consultant frames the problem. A forward-deployed team builds the system and runs it until it works in production. Who does what: ornsoft.com/blog/forward-dep…
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Researchers at Crissy Field identified 159,041 projects built with Lovable; on 24,664 sites, database records came back with no login, they report (read-only, sample not representative). Whoever builds it, check four things before go-live: linkedin.com/feed/update/urn…
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Sources: crissyfield.de/research/lova… (covered by Handelsblatt, Nov 2: handelsblatt.com/technik/ki/…)
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An LLM eval is a fixed set of test cases with agreed criteria, run on every change, that tells you if the system got better or worse.
Without one, every pilot error reopens the debate: is it good enough? With one, the question has a number and a date.
ornsoft.com/blog/what-are-ll…
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Un contrôle ne demande pas seulement si la pièce est au dossier : il demande ce que vous avez vérifié, sur quelle preuve, et qui a décidé.
Voici les cinq éléments à conserver avec chaque vérification pour un dossier de preuve qui tient :
ceertia.com/fr/blog/piste-au…
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AI trusted by design: governance built into the operation.
Permissions, approval gates, traceability and monitoring, built in before go-live.
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The full article: ornsoft.com/blog/trusted-ai-…
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How enterprises use forward-deployed engineering to move AI from pilot to production.
Who the engineers work with, what they own and how the security review gets done.
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The full article: ornsoft.com/blog/forward-dep…
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