Ascend.io - Advanced AI for building & running agentic data & workflows
by•
Meet Otto, your AI data teammate 🐐 — the agent that builds, monitors & fixes your data workflows. From pipeline health to schema evolution, Otto helps you ship data products in hours, not weeks.
Replies
Ascend.io
Hey Product Hunt! 👋 I'm Sean, the founder & CEO of Ascend.io. I've spent 20+ years in data systems at Google, Ooyala (the first company I founded), and now Ascend. 🚀
Today we're launching something that makes working with data truly delightful. Whether you're a data engineer, analytics engineer, or anyone building data products, I think you're genuinely going to love Ascend.
The vision: What if you had an AI teammate that helps you build, monitor, and fix your data workflows? Not just code suggestions - an actual partner that understands your data and takes action.
Meet Otto, your data GOAT 🐐 (and yes, the greatest of all time)
Otto is your AI agent that co-builds with you. Think of him as the teammate who:
1️⃣ Monitors pipelines 24/7 and catches issues before they become problems
2️⃣ Suggests tests based on your business logic
3️⃣ Connects to your tools (Slack, PagerDuty, GitHub) to coordinate incident response
4️⃣ Actually fixes things autonomously when he's confident
But here's what makes this different: Your workflows are unique. Your agents should be too.
🤖 Custom Agents: Build domain-specific agents in minutes for dealing with things like schema evolution, cost optimization, data quality, compliance - whatever your team needs
⚡ Works with Your Stack: Snowflake, Databricks, BigQuery, Azure, AWS - Otto makes your existing platforms even better
🚀 Real Results: Teams are already shipping data products in hours instead of weeks.
Try it free at app.ascend.io/signup (no credit card required, and you can set up your first agent in 5 minutes)
I'm genuinely curious: If you could have an AI agent handle ANY part of your data workflow, what would it be? What would free up your time to build the stuff you actually care about?
Also for Product Hunters: Extended free tier + early access to new agent capabilities. I'll be here all day talking about agentic workflows, how we think about AI safety in production, or just nerding out about data! 🤓
Ascend.io
Great work from Team Ascend! Curious @sean_knapp, what do you think some of the more interesting use cases data teams should consider for leveraging AI?
Ascend.io
@jenny_hurn There are so many!
Otto DataOps: have Otto handle pipeline breaks, error triaging, and notifications for you.
Co-pilot: just like Cursor, but for data! Let Otto do the heavy lifting of analyzing code, inspecting data, prototyping, and more. According to my usage stats, I had over 30 conversations with Otto this weekend alone. 🤓 Bonus: Otto's really good at making bulk edits for you. 😮💨
Data migration: we've seen customers use Otto to not only migrate data clouds (say, from open source Spark to @Snowflake), but also off of legacy systems like Informatica and even dbt + Fivetran.
Weekly Snippets: forgot what you did last week? No worries, Otto scans Git history for you and can whip those up for you in less than a minute!
ScaryStories Live
@sean_knapp Congrats on Otto, love the “agentic” angle. Quick Q: how do you validate and roll back autonomous fixes across heterogeneous stacks (Snowflake/Databricks/BigQuery), and what’s your highest-signal alert beyond generic pipeline failures?
Ascend.io
Great questions @tonyabracadabra!
How do we validate & roll back autonomous fixes? We have a ton of DataOps features built into Ascend that help make deploying & rollbacks easy. There is a ton of configurability for advanced users, but by default, every workspace & deployment pairs with a separate git branch, and unless you specifically configure it not to, we isolate data between these environments (you know, so your dev workspaces doesn't overwrite prod). This, combined with data quality tests and some other helpful features make it particularly easy & safe.
As to highest signal alert, beyond outright failures, we've found a few:
Data quality checks: we all put assumptions into our code... these help us validate those assumptions and catch breaks before they spread. Otto is also really good at adding these for you. 😉
Processing time: if this spikes from run to run, something likely is going on. Otto (and you, of course) have access to full historical run history for every flow and component, and can easily run comparisons to catch when things change.
% of data needing to be reprocessed: we have a nifty feature called "Smart components" that optimize processing by tracking data lineage and fingerprints. For these components, if you see a large % of smart components needing significant processing, this can be an important signal.
Ascend.io
Interested in a quick interactive tour? Check it out: https://ascend.storylane.io/share/o2awn77kz0ut
Ascend.io
@jenny_hurn the UI looks so good! I love how quickly you can go from signup to running data pipelines and using Otto
Ascend.io
@codydkdc Thanks Cody!!
Ascend.io
Can't wait to see what developers will build on the one and only agentic data engineering platform!
Ascend.io
Sharing the brand-new product tour video so people can see Ascend in action, making data engineering delightful:
Can Otto be customized with additional rules to help with company specific requirements (ie. code, logic..)?
Ascend.io
@tessa_juengst Hey Tessa! Yes! Otto is extremely customizable. Here are links to a couple docs to check out!
Custom Agents
Custom Rules
Hey Sean @sean_knapp ,
Congrats on launching Otto! Love the agentic approach. Data teams definitely need this help.
How's the launch response been? What marketing strategies are you focusing on?
Curious how you're reaching data engineers. Would love to hear your approach!
Ascend.io
Hey @mfarhan1107 , fun question! I think one of the biggest things we've learned is that data engineers would much rather build something cool sit through a pitch. We're hosting a Hands-on Lab on Wednesday and have record breaking numbers of registrations. :D
This is interesting! Can this chain multiple agents for complex processes, and how customizable are integrations for devs?
Ascend.io
Hey @sneh_shah, thanks for checking out the launch!
Yes! Users can chain together multiple agents (&/or non AI-driven automations) to build custom workflows. And it's pretty easy to connect agents to external tools via MCP servers for super custom integrations. (We're talking a couple lines of YAML to give agents the ability to work directly in existing tool stacks)
It's pretty cool to consider what is possible with this kind of flexibility! Really the only limit is human innovation. But we have customers building systems that respond to incidents, suggest code to patch deploy to fix errors, and basically have PRs ready to go before on call even gets back to their laptop.
If you're interested in checking out some docs to see an example of how this works, I'd recommend checking this one out for sure. (Also, huge shoutout to @shifra_williams for building & maintaining our beautiful docs!)