Hi HN, we're Harshith, Manoj and Manik and we're building Tegon (
https://github.com/tegonhq/tegon), open-source issue tracking software that uses AI to smartly automate manual workflows or provide more context to engineers for a given task. There's a demo video here:
https://www.loom.com/share/b664b01e9b064a02be5791c12b77a107, and you can try out the product at
https://demo.tegon.ai using these credentials:
Email: elon@xyz.com
Password: XfFNw6GwVJVQv6PA
As engineers, our experience with traditional tools like Jira hasn't been great. It is slow, bloated and often acts as a burden to engineers. These tools didn't help engineers in getting the work done faster, they only helped the management in tracking the work which enabled a lot of processes and micro-management which used to kill our productivity.
With the rise of LLMs, we thought about how project management and issue tracking would look 5-10 years from now. The current tools didn't match our vision, which excited us and started the journey of Tegon. We aim to build a tool where manual workflows are either automated or handled by AI. This tool will provide better context about a task to an engineer by smartly gathering data from all sources, helping teams with better prioritization.
Tegon loads all the data from local (indexed db) thus making it super fast to load and navigate. We make all of this happen by real-time sync in the background. Tegon also uses AI to simplify the issue-creation process by automatically creating titles, suggesting labels and assignees and identifying duplicates.
Tegon also simplifies the issue creation process from Slack, just apply an emoji to a Slack message and a tegon issue will be created making it easier for other teams to raise bugs or feature requests to engineering teams.
We deeply value the feedback from this community and have spent the last month revamping Tegon's design based on the feedback from our last launch. We just got started and there's a lot more to come. We're eager to get more feedback and keep building. Let us know what you think in the comments :)
I realize AI is the hype right now and it seems like most products have to pay the AI Tax (i.e. "Yes we're doing AI stuff so you should <buy/sell/fund/etc> our stuff"). But "AI" is a nebulous category, and when a product bills itself as "<Noun>-first", it sets up an expectation that <Noun> is fundamental to the product, i.e. if you stripped all other aspects of the product away, what's left at the end is <Noun>. But I have no idea what that means in the context of the current "AI" hype.
Based on your demos, you've built a fairly standard looking ticket tracking tool that has some AI features. And those are features that every incumbent in this space started adding to their products years ago or are actively doing it now.
I mention this not because I'm trying to say your product doesn't have value, but because the way you're positioning this doesn't make a lot of sense to me. As a prospective buyer, if I'm already using an existing tool, the moment I start digging deeper to know what "AI First" means, I'll find that what this really means is "Jira but with some AI features on top", which isn't very compelling when my <Vendor> account team has been telling me all about their new AI features that I can start using on all of my existing data as soon as I upgrade, no 6-18 month migration required.
If I'm a frustrated customer of those products, AI is not the reason I'll be looking to switch, and I'd be far more likely to be interested in performance, extensibility, openness, integration capabilities, etc.
Maybe that's not the type of customer you intend to target, but if you hope to reach them, I leave this as food for thought. Best of luck to you.