Fast. Accurate. Verified by real experts. Power your product with human-grade intelligence.
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Joined April 2012
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Big funding doesn’t guarantee job security.
Pearl CEO Andy Kurtzig tells Forbes why candidates should look beyond the headline: “Investors giving a company money is not the same as customers giving it money.”
Full article in comments
Newer and bigger models aren't automatically better at expert work.
Pearl benchmarked 48 frontier models across business, law, health, and tech against verified expert judgment.
Results below.
RAG grounds answers in current business data. Agents take bounded actions across systems. Experts handle high-stakes ambiguity.
Commercial AI works best when each has a clear role and escalation is built into the workflow.
When an AI chatbot gives a customer the wrong answer, they blame your company and not the model.
Here’s how to improve AI answer accuracy before responses reach customers.
they finally cracked why 2+2=5
We are entering a new era of discovery now:
openai.com/index/sharing-ai-…
The WHO called for stronger ethics oversight of AI in health research.
Compute generates options. Patients are not prompts.
Verification by credentialed experts is where liability and safety live.
The biggest labs are figuring out what high-stakes industries knew all along.
Compute generates options. Verified domain experts deliver truth.
Human in the loop is the entire ballgame. Kudos to OpenAI.
We’re working with an independent advisory group of mathematicians to help OpenAI responsibly share advances in AI and mathematics.
The group will advise on how we assess and communicate new mathematical results, uphold academic and professional standards, and build tools that support mathematical research and learning.
Through this work, we want mathematicians to be at the center of shaping how AI supports mathematical understanding and how its benefits reach the wider community.
openai.com/index/advisory-gr…
OpenAI launched Astra for Law.
Frontier models entering legal confirms where enterprise AI is heading.
In high-stakes workflows, a faster model without expert verification just accelerates risk.
The moat is expert accountability before anyone acts on the output.
If an AI agent gives advice that gets a company sued, who is actually accountable?
The engineer who wrote the prompt, the model provider, or the executive who approved deploying without human review?
Retail CRO spends millions optimizing button colors and checkout steps.
Yet the biggest drop-off for high-intent shoppers happens much earlier:
Right on the product page, the exact second an unanswered question stalls the purchase.
Pairing conversational AI with real-time human expert verification bridges that gap.
Shoppers get the accuracy of an in-store specialist at digital scale, right when they are deciding whether to buy or bounce.
When you eliminate purchase hesitation before checkout, conversion follows intent.
Full benchmark breakdown and methodology:
pearl.com/post/pearl-s-30-en…
