Akur8 builds the OS for insurance pricing - our SaaS platform helps 320+ insurers worldwide model risk up to 10x faster using transparent ML.
We're hiring an AI Engineer to join our team. We're building systems that transform tens of millions of messy, unstructured regulatory documents into actionable intelligence. If evals, agentic fine-tuning, and agent orchestration are the problems that light you up - not just things you've read about but things you actually have opinions on - we'd love to talk.
The team is small and talent-dense. You'll ship to production, talk to real customers, and have genuine ownership over what you build.
There's a potentially amazing use case here around parsing PDFs to markdown. It seems like a task with insane volume requirements, low budget, and the kind of thing that doesn't benefit much from autoregression. Would be very curious if your team has explored this.
The vast majority of people don't need smarter models and aren't willing to pay for a subscription. There's an argument to be made that ads on free users will subsidize the power users that demand frontier intelligence - done well this could increase OpenAI's revenue by an order of magnitude.
This is going to be tough to compete against - Anthropic would need to go stratospheric with their (low margin) enterprise revenue.
This is a hand wavy article that dismisses away VLMs without acknowledging the real world performance everyone is seeing. I think it’d be far more useful if you published an eval.
Congrats on the launch - you're value-add is quite confusing as someone that's at the applied AI layer. This comes off as more of a research project than a business. You're going to need an incredibly compelling sales pitch for me to send my data to an unknown vendor to fix a problem that might be obviated by the next model release (or just stronger evals with prompt engineering). Best of luck.
I'm not sure if they're gearing up for an announcement, but about 9 days ago they dropped the preview warning from their README. I'm assuming they're still working through final housekeeping items before formally announcing it.
Seems like their critique boils down to two areas - pandas limitations and fewer built ins to lean on.
Personally I've found polars has solved most of the "ugly" problems that I had with pandas. It's way faster, has an ergonomic API, seamless pandas interop and amazing support for custom extensions. We have to keep in mind Pandas is almost 20 years old now.
I will agree that Shiny is an amazing package, but I would argue it's less important now that LLMs will write most of your code.
If cloudflare goes down, you can blame them. If your hand rolled solution fails when cloudflare exists, you’re going to have a tough pitch to leadership why you’re in charge of the technical roadmap. Choose your battles, and this is not a hill worth dying on.
Akur8 builds the OS for insurance pricing - our SaaS platform helps 320+ insurers worldwide model risk up to 10x faster using transparent ML.
We're hiring an AI Engineer to join our team. We're building systems that transform tens of millions of messy, unstructured regulatory documents into actionable intelligence. If evals, agentic fine-tuning, and agent orchestration are the problems that light you up - not just things you've read about but things you actually have opinions on - we'd love to talk.
The team is small and talent-dense. You'll ship to production, talk to real customers, and have genuine ownership over what you build.
Come join us at https://jobs.ashbyhq.com/akur8. Mention in your application that you saw our post on HN.
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