Software to give insurance advice like an agent would
Chris, Dan, and the team at Goodcover here. Goodcover is building a new home and renters insurance co that tries to fix the insurance incentives by returning any unclaimed premium back to customers, keeping a fee instead. Goodcover was YC S17, but off the record due to discussions with the CA government. And we’re still “pre-launch” - starting a new insurance co is hard as it turns out! Part of the technical challenge we deal with is, how do we build software that can scale what an agent does? Although we can’t offer a full insurance experience yet, we thought we’d roll out an advice app…
What it does
In the maker’s words, at launch
Chris, Dan, and the team at Goodcover here. Goodcover is building a new home and renters insurance co that tries to fix the insurance incentives by returning any unclaimed premium back to customers, keeping a fee instead. Goodcover was YC S17, but off the record due to discussions with the CA government. And we’re still “pre-launch” - starting a new insurance co is hard as it turns out! Part of the technical challenge we deal with is, how do we build software that can scale what an agent does? Although we can’t offer a full insurance experience yet, we thought we’d roll out an advice app (https://app.goodcover.com/advice) that makes a stab at giving advice like an agent might, but using software. By analyzing your current insurance docs, we can: - Benchmark the coverage you have against what is “normal”. - Provide advice about some specific things that you can fix or at least consider fixing. - Arm you with information on things you can push back on with your insurer. Technically, the way it works is we’ve generalized some gotchas, manually looked over a bunch of Home/Renters policies, and built a workflow for us to select where we think you are in the homeowners/renters spectrum. So it’s really just workflow automation, however, it requires obviously being able to translate insurance constructs to user things, but most of it is pretty simple from an automation standpoint. Most of our time is generally spent on building out insurance functions, but it’s been a great experiment in information hierarchy to try and reduce complex concepts and insurance-speak down to actionable pieces of information for customers. No obligation, and feel free to take our advice back to your current provider and get stuff fixed. Goodcover Insurance Solutions LLC is licensed in California (0M20813) so if you are not in CA we can still have a look, but you should definitely review our advice with a pro in your state.
Does the same job
all alternatives →
- WBWe built a care home software2022 · carehomedomestic.com · ▲6
My other half runs a care home in the UK. She was frustrated with some of the remaining paper based processes, and the 'techy' alternatives were off-putting. So we built Care Home Domestic. The project is self funded and has been a fun and exciting journey! It is currently in use at a few homes and feedback so far is really good. There's loads of work still to do, but we've gone out early and aim to be reactive to the feedback of our users.
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, July 2018
the whole month →- BA
Life & fun · 2018 · brow.sh
- TR
Dev tools · 2018 · github.com
