HyperArc
The First AI Native Business Intelligence
332 followers
The First AI Native Business Intelligence
332 followers
HyperArc is the first AI-native BI platform that learns from your team. Ask questions in plain English, get trusted insights instantly. Built by Tableau and Einstein Analytics veterans. Fast, secure, auditable insights—no SQL skills needed.
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Launch Team
Render Sandboxes: a computer for every agentGive every agent its own machine. Starts in under a second
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Hi Product Hunt Community, I’m Tristan, Co-Founder of HyperArc!
The Problem:
Getting actionable insights from your data is time-consuming and complex for many reasons. You have to start by understanding the data, business logic, and relevant schemas just to get started. After spending hours on an analysis, you end up with a dashboard — but the hard-earned reasoning and knowledge that led to those insights remains locked in the analyst’s mind.
Then, the next time you’re faced with a new analysis, you repeat the process. That’s why your seasoned analysts are so invaluable — it’s the intuition they’ve built up over years of exploring your data.
But what if your BI tool could retain that knowledge for you — acting like an analyst sitting alongside you, learning, observing, and helping?
How HyperArc is Different:
📘 A Notetaker for your Analysis
As you dig through your data, HyperArc summarizes and remembers the analytical path paired with rigorous statistical analysis and summarization. We capture the intuition behind the analysis — in Memories.
⭐️Accessible to All
With the knowledge about your data and how you use it captured as Memories, analytics finally becomes accessible to all. Shoulder tap your virtual analytics agent with questions about not only the data, but how you do analysis in natural language through questions and suggestions. Better yet, unleash the agent to run analysis for you — all backed by Memories relevant to your data.
Go beyond just enabling just humans and empower AI agents with your analytical knowledge through the HyperArc MCP server with semantic search for Memories and insights.
🚀AI for Analytics from the Ground Up
From building Salesforce’s Einstein Analytics — which learned from all the metadata and language inside Salesforce to power semantic search and questions — we saw the gaps in the language data needed to power AI for analytics. HyperArc takes the next step by going beyond simply consuming language — it generates it through Memory synthesis.
AI is built into every step — from prepping dataset metadata to make it AI-ready, to leveraging chain-of-thought Memories for suggestions with graph RAG.
Who It’s For:
Analysts that want to be accelerated by the Cursor for Data with AI augmented analysis and suggestions in a new UX for data built for AI.
Teams that want analysts that can answer questions or help 24/7 through agentic exploration.
Organizations that want to codify the most valuable artifact of analysis, the intuition of analysts, into institutional memory that is accessible to all, from humans to agents.
Try HyperArc Today:
See the types of questions we can help answer with our public datasets: https://app.hyperarc.com/#/home
Sign up to upload your own datasets and watch HyperArc build context and insights in minutes.
Ready for scale? Paid plans plug straight into Snowflake, BigQuery, Redshift and more.
👉 Sign up at hyperarc.com – we’d love your feedback and questions below! Thanks for hunting 🧡
@tao_tristan can non-tech team members (like marketing or ops) safely ask HyperArc questions without risking pulling the wrong numbers? Would love to see some use cases on that. btw Congrats!!!
@hamza_afzal_butt this was a top concern for us as well and why we believe text-to-sql LLM wrappers is not all you need!
All HyperArc answers are grounded by your most relevant memories. This is so we can automatically learn and show the right numbers as well as let non-tech team members know what can't be answered or has not yet been clearly defined by those that know the data better.
Those more curious can always choose to "Continue Exploration" where we will try to fill in the blanks and get users started in our no-code query builder that has both traditional drag and drop, natural language, and agentic exploration.
@hamza_afzal_butt We also build a statistical kernel which helps keep things grounded, too. Our MCP can also help ping the analyst who generated the memory to close the loop. We're building the analytics operating system that sits between all of your team members, analysts and non-tech members alike!
@tao_tristan Hi Tristan,
I’m Nima, founder of Bestofweb .site, a directory of great tools. Congrats on the launch of Leada. Capturing analyst intuition as reusable “Memories” is a smart and needed shift in BI. adding it to Bestofweb .site too.
@nimaaksoy Appreciate your support!! Bestofweb seems very cool!
This is a serious leap forward for BI tools. HyperArc's ability to learn from analysts’ thought processes and retain context is what sets it apart—no more starting from scratch every time. Love the focus on 'Memories' as a core feature. This kind of intuitive AI is exactly what the industry needs to close the gap between data and action. Big win for teams drowning in dashboards but starving for insights.
@suryansh_tiwari2 we appreciate the kind words! We agree that intuitive context is the the next frontier in enabling AI to effectively operate with BI. We're excited to continue to pioneer it via Memory with the support of the Product Hunt community!
Great idea! It sounds like ai tools such as powerdrill, julius. Hope yours can outperform them!
this is so awesome. excited to never have to remember complex BI terminology again!
@jason_chernofsky That's what we hear from our users, too. Thank you for the kind words! BI shouldn't be this complicated!
Really like how HyperArc makes BI more accessible with natural language queries. Curious—how does it handle data privacy and compliance, especially for industries with strict regulations? Congrats on the launch!
Thanks @patpijanowski! We're SOC II compliant and have a sharing model much like GitHub with organizations and projects (repos). Projects can be public for embedded use cases, but default to private within your org where you get full control with user group sharing.
All datasets, dashboards, queries, and memories belong to a project so you get fine grained control over what gets shared and what gets used when answering questions with natural language with the ability to scope questions and suggestions down to knowledge captured in specific projects.
@patpijanowski We've got the SOC Cert and recent clean Pent test results for our customers to access. We used @Thoropass and @Oneleet which was were great vendors that we'd love to shout out!
Really impressive work! Love how Hyperarc makes AI-powered video editing so much more accessible and efficient. Can definitely see this becoming a go-to tool for creators. Wishing you a solid launch and lots of love from the community! 🚀
HyperArc seems revolutionary! The idea of capturing analytical intuition and making it accessible to all is genius. The AI-native approach and ability to ask questions in plain English make it incredibly user-friendly.