What will it take for enterprises to run software engineering like AI-native companies?
Today, we are announcing Autoheal’s (@autohealai) $𝟳.𝟵𝗠 𝘀𝗲𝗲𝗱 𝗿𝗼𝘂𝗻𝗱 to help make it possible 🚀
This funding will help us expand our go-to-market team, accelerate enterprise rollouts, and strengthen the platform reliability and customer support that enterprise adoption demands.
Our thesis is simple: enterprises need 𝗮𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝘀𝗲𝗹𝗳-𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁 and 𝗳𝗶𝗻𝗲-𝗴𝗿𝗮𝗶𝗻𝗲𝗱 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 working together to trust agents with more engineering work.
That’s why we built Autoheal: a 𝘀𝗲𝗹𝗳-𝗶𝗺𝗽𝗿𝗼𝘃𝗶𝗻𝗴 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗳𝗮𝗰𝘁𝗼𝗿𝘆 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲.
We provide prebuilt, cloud-based worker agents for incident response, vulnerability remediation, and AI coding cost efficiency. We also provide the sovereign infrastructure enterprises need to build and continuously improve agents across the post-coding SDLC, all within their security boundary.
Here’s how the self-improvement loop works:
↳ 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗲. Analyze agent traces against signals from code reviews, CI failures, and production incidents.
↳ 𝗜𝗺𝗽𝗿𝗼𝘃𝗲. Turn those signals into proposed changes to agent skills, prompts, tools, or model selections, then check historical benchmarks for regressions.
↳ 𝗚𝗼𝘃𝗲𝗿𝗻. Engineers control access, govern actions, and approve changes to agent behavior. Those changes are version-controlled and auditable.
The goal: free engineering teams from 𝗽𝗼𝘀𝘁-𝗰𝗼𝗱𝗶𝗻𝗴 𝘁𝗼𝗶𝗹 so they can build more revenue-generating software.
We couldn't do this alone. Thank you to Harpinder Singh (@hmadan) at Innovation Endeavors (@iendeavors) for leading the round, alongside Anupam Rastogi (@anupamr) at Emergent Ventures (@emergent_vc), Kim 💚 Moore (@MooreKimJ) at U&I Ventures, Amir Shevat (@ashevat) & Raphael Danilo (@raph_danilo) at Darkmode Ventures, Dheeraj Pandey (@dheeraj) & Amit Kumar at Param Hansa Values LLC, and Quang Hoang (@qhoang09) at Batch Ventures (CTO Fund).
We are also incredibly grateful for our key angel investors: Shawn Kung (@shawnykung), Sumeet Arora, Anshu Sharma (@anshublog), Savin Goyal (@SavinGoyal), and Srikant Gokulnatha (@gosrikant). Thank you for backing our vision so early.
A heartfelt thank you to our special customers: Sameer Jain at Nomura Bank, Krish Shetty at AvidXchange, and Vijay Pendyala at Empiric Earth for helping us turn our shared conviction into a product.
And to Team Autoheal: thank you for earning our customers’ trust and building an incredibly deep product in such a short time.
For leaders already expanding agentic engineering beyond coding, what gives you the confidence to trust agents with greater autonomy? I would love to hear what’s working and what’s still missing.
Me today: the founder who refreshes Product Hunt every 5 minutes.
After a very long launch day, we’re still #2 🫠
If you haven’t checked out Tadata's launch yet, now would be an excellent time:
https://t.co/NopPz0ewgc
tl;dr - Tadata is live on Product Hunt today.
Come support us with an upvote/comment ❤️
https://t.co/mPyO9LYXtF
Some thoughts on why we’re launching now, and why the world apparently needed yet another AI employee in Slack 👇
tl;dr - Tadata is live on Product Hunt today.
Come support us with an upvote/comment ❤️
https://t.co/mPyO9LYXtF
Some thoughts on why we’re launching now, and why the world apparently needed yet another AI employee in Slack 👇
Tadata is live on Product Hunt today. Come support us with an upvote/comment ❤️
https://t.co/UrlrM58hKs
Using AI at work should feel like delegating to a great teammate, not learning how to build and manage agents.
Tadata reads the room.
Tadata is launching on Product Hunt today!
Most AI employees have a lot of tools.
Fewer have judgment.
Tadata lives in Slack, gets your work done across your tools and hard to reach parts of the web, and delivers back the answer instead of the essay.
We'd love your support and feedback!
We’re launching @tadata_hq on Product Hunt today, so naturally we made a tiny arcade game
Play to unlock a Tadata discount code
https://t.co/P3uH7EYbzM
WAIT PLEASE TELL ME OPENAI PARALLELIZED RECURRENT DEPTH.
Microsoft Research already showed us in June that you can run K latent blocks in parallel for R recurrent iterations. LoopCoder has also scaled recurrent depth to 40B parameters in July + a few others.
But NOBODY has publicly deployed this architecture in a frontier class commercially available model anywhere near this scale (1T+) . If Astra is doing width × depth at frontier scale instead of simply looping one latent state, I’d expect some big benchmark jumps.
Your CRM already knows which deals went quiet.
It just has no way to tell you, and no way to do anything about it.
Tadata connects to Salesforce today. It proactively finds opportunities, and automatically keeps Salesforce updated.
"4 accounts in your pipeline haven't been touched in 21 days. Want me to draft the follow-ups?"
"I updated all opportunities with details from your calls today."
You just say yes and Tadata does the work. You never have to open Salesforce.
Free to start, $50 in credits: https://t.co/PxpRmKCnOw
Everyone thinks the markdown → HTML push is about more output tokens. That's marginal money.
The real money is making every dev rebuild their markdown viewer pet project as an HTML viewer.
Game on, Anthropic. I shipped mine: https://t.co/dU4wG4uMVB
Excited to announce Tadata's partnership with @tavilyai!
We’ve launched an MCP server that helps developers integrate Tavily’s API faster, smarter & with built-in AI guidance. It's already handling thousands of calls across dozens of MCP clients.
Thanks @rweiss57@DustinPulver @LTzanani!
Read more in our blog: https://t.co/OMl1iBQvHo
Here’s the story of how we started Tadata—and what we’re building now at https://t.co/21YexWTGHq.
From an open-source project with 200K downloads to a full platform for MCPs, we’re helping people connect software to AI.
Built with @makhlevich, @tadata_it, and @ThatsShahar
Engineers ask us: “What’s the delta between our API and an MCP?”
Published a blog breaking it down 👇
🧠 Why APIs make bad MCPs (shoutout to @davidgomes, @zeeg, @david_soria_p)
⚡ Start there anyway
🚀 How Neon, Stripe, and Tavily take it further
🔗 https://t.co/23tJSvTYjy