Show HN: Workflow86 - An AI business analyst and automation engineer
23 comments
·January 30, 2025antidnan
Random but I love the name. I feel like we've entered into a new fun era of startup names. No more ___ly or ___ist etc. This era is generic word/noun + arbitrary numbers or letters after it.
I think ChatGPT really kicked that off, but maybe it was something else that inspired it?
Less normie/friendly and more technical sounding. So far, I'm a fan!
taaron
Partially inspired by WD-40 but more so the exorbitant price for anything workflow.com. The number did have some logic behind it: 8 letters in automate and 6 in no-code.
jackmorton
Curious as to how this stacks up to some of the other AI copilots, I think Make and Zapier kinda have something similar?
taaron
Our AI goes much further than the copilots both in terms of its ability to go from a user prompt or requirement to a complete, ready-to-run workflow.
Make's copilot is pretty limited to generating an outline of the flow by selecting the right nodes but does not actually configure them. You still need to manually click into each one and set it up.
Zapier goes a bit further than Make, but it still leaves the workflow with a lot of configuration work that needs to be picked up by the user.
In both Make and Zapier, you really need to prompt the AI copilot in a very specific way to get good results. In our case, the AI is designed to use its business analyst/consultant mode to extract information so it can work from very general, unclear and ambiguous instructions to a clearly defined workflow/process to build.
The ability for our AI to edit the workflow at any time (including on top of your own manual changes) also means you can have a continuous iterative dialog/interaction with our AI copilot vs a once off interaction at the start. Both Make and Zapier's AI Copilots lack this or are very weak in being able to edit existing workflows reliably.
MattDaEskimo
What exactly is "your AI"? From how you describe it, it's a GPT model with a "You're a business consultant" prompt.
I'm sorry to be rough, but from your description it just sounds like your AI somehow does a better job with prompts compared to Zapier & Make, which is highly subjective.
Besides that, this looks very cool and IMO is the future of interfacing AI automations in work environments
null
causal
Slick UI, curious how practical the workflows actually are. My suspicion is that this is automating the part humans would want to do (designing the workflow), whereas most of the hours put into workflow automation is integration (90% of which is not going to be a clean REST API).
That said, maybe this would be really valuable to someone doing a greenfield project without needing to back into existing workflows. Either way, cool project.
taaron
Integrations are definitely the toughest part of the implementation. That being said, I'm pretty optimistic on (1) AI getting better at writing the code/REST API calls or making it a lot easier or (2) the sort of browser agents we've seen with Open AI Operator, Claude Computer Use etc get good enough to integrate via the UI layer vs the API level.
taaron
Some new users are encountering issues with the AI during onboarding - if you do encounter an error, you can always try out the AI again by just click the glowing purple button on the right of any workflow canvas! This seems to be due to some rate limit issues from the uptick in self-serve sign-ups and hopefully should be resolved soon.
todsacerdoti
You should add 2500 app integrations to Workflow86 via Pipedream Connect -- https://pipedream.com/connect
taaron
Very interesting will definitely check it out!
bananamansion
are you using n8n for the workflow builder?
taaron
Nope, we built the workflow builder entirely ourselves, but I guess most workflow builders do end up looking very similar!
causal
That strikes me as a surprising choice given the amount of prebuilt integrations with n8n
taaron
One factor in hindsight for doing this in-house was we did find out that AI can struggle with understanding and navigating existing workflow builders that were built and optimized for human usage and comprehension e.g. what nodes are available, the options that can set inside of those nodes and even how they are named had quite an impact on whether the AI could reliably form valid workflows on its own.
bushido
Not that surprising if you take n8n license into account. Its very prohibitive.
65
How is this better than Zapier?
taaron
Because we started with a focus on orchestrating forms and tasks, I'd say we're more suited for complex, long-running workflows that involve a lot of stop/start steps assigned to different teams (e.g. review and approvals) mixed with automation in between.
We actually integrate with Zapier i.e. you can trigger a workflow from Zapier, and we can trigger a zap from within a workflow.
While Zapier has also done some great work in the AI space, I'd also say our Ai builder goes a lot further in being able to fully set up a workflow and then continue to help users edit, change and refine them at any point. We're able to do this because a lot more of the moving parts are internal to Workflow86 (forms, tables, tasks etc), so the AI has more context and control over what it can do.
chinathrow
Looks like your product might be a perfect acquisition target for Zapier then ;)
ttul
Oh god, anything would be better than Zapier. They are so laden with legacy bloat; their UX is slow and cumbersome. A classic case of enshitification.
null
Hey HN,
We built Workflow86 to help teams build and automate their internal business processes and workflows using drag and drop components like forms, tasks, tables and nodes for business logic, API requests, running custom code etc. It works as a standalone process/workflow automation tool, or as a workflow customization layer on top of existing apps and systems like HRIS, CRM and ERP.
One common problem we hear from users is that no-code still has a significant learning curve, and it can take some time to understand how to properly build something. Users also needed help with knowing what to build in the first place, or what a process might or should look like.
To solve this, we've integrated an AI that acts as a business analyst/consultant and workflow automation engineer. This AI is powered by a combination of Large Language Models and lots of prompt engineering, RAG and prompt chaining techniques we developed along the way.
See a demo of it in action here: https://www.loom.com/share/fdbd5ad64c8f4071a062ecaa6a6d01f1?...
In business analyst/consultant mode, the AI helps users brainstorm ideas, identify and discover processes and draft what a process should look like. Like a business analyst/consultant, the AI works to pull and extract information and details from the user by asking the right questions rather than rely on the user's instructions alone.
Once the required information has been gathered, the AI goes into engineer mode: it will plan and then build the entire workflow by selecting the right nodes, connecting them together and then fully configuring every single node individually as well. This includes writing custom code and API requests using stored credentials when required.
Once a workflow is built, edits can be done manually or by asking the AI to adjust the workflow at any time (e.g., “Add a compensation band check before final approval”). The AI has full context of the current state of the workflow, so it can “patch” in any changes like adding new nodes, rewriting existing nodes and so on.
Some use cases we’ve seen from customers include building: - automated compliance checks for new CRM leads - custom international contractor onboarding workflows on top of a HRIS - automated vendor risk assessment before ERP updates
Try it out and let us know how the AI performs and any other feedback you have!
Full docs can be found at https://docs.workflow86.com