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dennisy 19 minutes ago [-]
Hey!
This looks great and congratulations on the launch.
I am also building in this space and wanted to get your views on a few things.
1. Are you building your own connectors to 3p systems?
2. How are you finding the sales motion? I found people to get the problem fast, but actually converting them seems rather slow.
Good luck!
kanyesrthaker 15 minutes ago [-]
Thanks! We build as much in-house as possible. We've found that this is the only way to really build an excellent end-user experience without putting any of the burden on the user. Regarding sales, we've found that the most useful thing has just been putting the product in people's hands and demonstrating that it gives upfront value. The hard part with memory is that most of the value comes with compounding, so we've had to get creative with how we can show in 5 minutes how Hyper lets you do things you couldn't do before.
dennisy 2 minutes ago [-]
Thanks for the replies!
Would love to swap notes at some point if you are up for it?
m_kovar 59 minutes ago [-]
Nice job! But here is my idea: why not build an agentic AI workflow that mimics the streamlined production methods of Ford in the early 20th century? We already have extremely powerful models and APIs, but we still tend to cram everything into one employee's workstation without giving out different tasks to different people.
kanyesrthaker 38 minutes ago [-]
Interestingly enough, this is how Hyper is structured under the hood. Rather than have one mega-agent whose job it is to go in and try to solve every problem simultaneously, we prefer a "production line" of narrowly scoped agents to make small decisions to keep the knowledge graph up to date. More broadly, agent orchestration is a problem tightly coupled to the "shared brain" problem. Definitely exploring what this means for Hyper as we grow.
ianpri11 2 hours ago [-]
Congrats on the launch!
How are you handling cases where multiple sources of truth contradict each other?
Does Hyper assume best guess or is there any human in the loop verification?
kanyesrthaker 2 hours ago [-]
The current conflict resolution is fairly simple: always trust humans, and trust recent human info more than old human info. We're very aware that as the knowledge system gets more complex, we'll need more sophistication, including:
- Human-in-the-loop verification
- Role-based ranking, i.e. be more skeptical when an intern contradicts the CEO
Unlike many other memory systems, Hyper never actually deletes memories. It constantly reranks them based on confidence, which factors into how they're retrieved. So every statement has a full history and system of record for how it got there, and you can trace (with attribution) why Hyper gives the answers it does. If there's something that Hyper misses, we provide tools in-app and in-terminal-plugin that let a human explicitly correct what Hyper knows.
implexa_founder 2 hours ago [-]
I totally support you guys so don't take it as a dig!
But isn't this mindblowing that while you were building and launching, Opus 4.8 launched and made a bunch of things you mentioned above irrelevant? for example, memory between sessions is way better, dynamic workflows will spin up a ton of agents to do work in parallel, and the ecosystem must provide better apis to be relevant (salesforce, uipath goind headless).
Again always support startups so cheering for you, but man things are changing so fast!
kanyesrthaker 42 minutes ago [-]
totally, honestly it's super inspiring to see how fast the field is moving. That being said though, I think there's a long way to go in this category. Efficient memory across tools, especially in a multiplayer/collaborative setting, is largely unsolved. And it's really hard to build something so elegant and simple that it appeals to all the people in the world that really have this problem, beyond the power-users in industries that already have high AI/engineering adoption.
Every new advancement from the model providers helps unlock new capabilities, but we are confident this "brain" idea is going to be core infrastructure for every company in the future. It extends beyond code and project management: we think about "what does the 'office of the future' look like? Ambient recording in every room? Smart whiteboards that turn drawings -> CAD -> kick off 3d printers?" and it's exciting to see how many unsolved challenges are on that road. Appreciate the support and excited to keep building :)
dbbk 18 minutes ago [-]
This isn't a business
shalinshah 14 minutes ago [-]
Curious what you mean, why not? Business is just a group of people creating a product or service so valuable people are willing to pay more for it than it cost to build. In what way do you think Hyper does not fit that model?
esafak 2 hours ago [-]
1. Have you measured the value provided by the knowledge graph layer over straight enterprise search (e.g., https://www.glean.com/) Benchmarks, please.
2. How do you deal with conflicting facts? In tech, the new is constantly replacing the old.
3. Is knowledge extraction real time? How fast is it in general?
shalinshah 1 hours ago [-]
Appreciate the thoughtful questions.
1. I'll address this in two parts.
(a) Memory vs. Enterprise Search. I consider search to address targeted, stateless retrieval whereas memory solves temporal, tacit, and derived problems. Glean can tell you why a ticket was filed or answer a specific question regarding a customer call. But in many companies, important questions are broader: "What went wrong the first time we went with this vendor?" "How has our brand shifted in tone over time?". These cannot be answered by a few documents, and it's not obvious whether this information would be in Slack or Notion or Drive. It requires an active, entropy-fighting system that is going to extract information and keep track of how it evolves over time.
(b) Benchmarks: absolutely. Don't want to claim anything before we've published results, but Hyper scores very well on LoCoMo and LongMemEval, and we are constantly trying to bolster our set of evals. We will publish results more openly in the coming weeks. I will caveat though: many SOTA memory providers are converging on the top end of these benchmarks, and yet we don't see mass adoption. We believe that UX affordances are underrated and critical to get "company brains" working in real, messy businesses. Many of our users have come to us from other providers purely because the competition was too difficult to use and maintain across the org.
2. Hyper maintains a graph of information where each node is an extracted "fact." This happens continuously, in the background, live from every connector or connected agent. At insertion-time, new information is compared against relevant information. Our system (a DAG of agentic nodes) determines the relationships between these facts and makes appropriate updates: X derives Y, A updates B. For now, we rely on recency as the primary indicator of conflict (i.e. we assume more recent information is generally more true than old information). We realize that this will need to become more sophisticated, and are iterating.
3. Knowledge extraction is real-time and asynchronous, and should add next to zero latency to any existing system. We continually update the graph in our backend, without relying on a nightly compaction/dreams cycle, so information from the world should be reflected in Hyper's responses in close to real time. Retrieval can be slightly more expensive, but the latency is negligible compared to the overhead of the calling agent. We recognize the importance of performance (we both worked on on-device robotics!) and are happy to publish numbers as we measure them :)
bensyverson 1 hours ago [-]
How are you planning to handle California's CCPA?
kanyesrthaker 1 hours ago [-]
Good question. User data is the right of the user. We don’t have automations for everything yet (we’re super early!) but any user has total right to request deletion, updates, or deliverance of their data, which we seek to comply with fully. You can find more information on our privacy and compliance progress here: https://heyhyper.ai/faq
nilirl 1 hours ago [-]
> The self-driving company brain
Made me think this was for companies working on self-driving.
shalinshah 58 minutes ago [-]
Yes that's super fair feedback, we're changing the wording soon :)
mycelos 2 hours ago [-]
[flagged]
robshippr 1 hours ago [-]
[flagged]
hiroto_lemon 2 hours ago [-]
[dead]
kanyesrthaker 2 hours ago [-]
Hey HN! Kanyes here, one of the cofounders of Hyper. Here all day to answer any questions :)
throw-hyper-01 2 hours ago [-]
Tried it, none of the integrations work, they do not connect, notion, slack, etc... I think you probably posted this a bit too soon, IMHO. :/
kanyesrthaker 2 hours ago [-]
Very strange, haven't seen this before. Could you shoot us an email at founders@heyhyper.ai with some more details about what you're seeing?
nils_transload 2 hours ago [-]
Congrats!!
kanyesrthaker 2 hours ago [-]
Thanks Nils!
zpoliczer 2 hours ago [-]
Congrats!
kanyesrthaker 2 hours ago [-]
Thank you! Very hot space right now and excited to be building in it
codelemons 2 hours ago [-]
congrats!
shalinshah 1 hours ago [-]
thank you !
MagicMoonlight 2 hours ago [-]
[flagged]
dang 1 hours ago [-]
Comments like this break the site guidelines - e.g. this one: "Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something."
- as well as the Show HN guidelines, which apply when people are sharing their work:
"Be respectful. Anyone sharing work is making a contribution, however modest."
"When something isn't good, you needn't pretend that it is, but don't be gratuitously negative."
You're welcome to make your substantive points thoughtfully, but please don't post like this.
This looks great and congratulations on the launch.
I am also building in this space and wanted to get your views on a few things.
1. Are you building your own connectors to 3p systems? 2. How are you finding the sales motion? I found people to get the problem fast, but actually converting them seems rather slow.
Good luck!
Would love to swap notes at some point if you are up for it?
How are you handling cases where multiple sources of truth contradict each other?
Does Hyper assume best guess or is there any human in the loop verification?
Unlike many other memory systems, Hyper never actually deletes memories. It constantly reranks them based on confidence, which factors into how they're retrieved. So every statement has a full history and system of record for how it got there, and you can trace (with attribution) why Hyper gives the answers it does. If there's something that Hyper misses, we provide tools in-app and in-terminal-plugin that let a human explicitly correct what Hyper knows.
Every new advancement from the model providers helps unlock new capabilities, but we are confident this "brain" idea is going to be core infrastructure for every company in the future. It extends beyond code and project management: we think about "what does the 'office of the future' look like? Ambient recording in every room? Smart whiteboards that turn drawings -> CAD -> kick off 3d printers?" and it's exciting to see how many unsolved challenges are on that road. Appreciate the support and excited to keep building :)
2. How do you deal with conflicting facts? In tech, the new is constantly replacing the old.
3. Is knowledge extraction real time? How fast is it in general?
1. I'll address this in two parts.
(a) Memory vs. Enterprise Search. I consider search to address targeted, stateless retrieval whereas memory solves temporal, tacit, and derived problems. Glean can tell you why a ticket was filed or answer a specific question regarding a customer call. But in many companies, important questions are broader: "What went wrong the first time we went with this vendor?" "How has our brand shifted in tone over time?". These cannot be answered by a few documents, and it's not obvious whether this information would be in Slack or Notion or Drive. It requires an active, entropy-fighting system that is going to extract information and keep track of how it evolves over time.
(b) Benchmarks: absolutely. Don't want to claim anything before we've published results, but Hyper scores very well on LoCoMo and LongMemEval, and we are constantly trying to bolster our set of evals. We will publish results more openly in the coming weeks. I will caveat though: many SOTA memory providers are converging on the top end of these benchmarks, and yet we don't see mass adoption. We believe that UX affordances are underrated and critical to get "company brains" working in real, messy businesses. Many of our users have come to us from other providers purely because the competition was too difficult to use and maintain across the org.
2. Hyper maintains a graph of information where each node is an extracted "fact." This happens continuously, in the background, live from every connector or connected agent. At insertion-time, new information is compared against relevant information. Our system (a DAG of agentic nodes) determines the relationships between these facts and makes appropriate updates: X derives Y, A updates B. For now, we rely on recency as the primary indicator of conflict (i.e. we assume more recent information is generally more true than old information). We realize that this will need to become more sophisticated, and are iterating.
3. Knowledge extraction is real-time and asynchronous, and should add next to zero latency to any existing system. We continually update the graph in our backend, without relying on a nightly compaction/dreams cycle, so information from the world should be reflected in Hyper's responses in close to real time. Retrieval can be slightly more expensive, but the latency is negligible compared to the overhead of the calling agent. We recognize the importance of performance (we both worked on on-device robotics!) and are happy to publish numbers as we measure them :)
Made me think this was for companies working on self-driving.
- as well as the Show HN guidelines, which apply when people are sharing their work:
"Be respectful. Anyone sharing work is making a contribution, however modest."
"When something isn't good, you needn't pretend that it is, but don't be gratuitously negative."
You're welcome to make your substantive points thoughtfully, but please don't post like this.
https://news.ycombinator.com/showhn.html
https://news.ycombinator.com/newsguidelines.html