I run an agency out of India which was limited till SaaS, Mobile apps, e-commerce, demand generation, etc. I’ve got clients mostly around USA, Australia and little bit in Europe as well. I’m not much of technical guy but I know how to market and sell very well.

I’m planning to expand into AI services, and looking for a trustable partner in India (No agencies please). We can initially work on some internal POCs (paid) and some project based contracts.

I’m open to partnering or co-running the AI vertical together in future if things workout well. I’m also open to discuss product/service ideas if you got.

i'm looking for a browser mainly for automation tasks like account management, testing, and running workflows. i've seen both 1browser and gologin mentioned, but i'm curious how they compare in terms of stability, profile isolation, and automation support.

if you've used either one, which would you recommend and why? are there any other browsers that work better for automation?

I've been trying to understand how AI outbound calling actually works because I'm seeing it mentioned more and more in automation project. From what I understand, there are a few pieces involved- the system making the calls, the AI voice handling the conversation, and the CRM tracking what happens afterward.

The part I'm still confused about is how these pieces usually connect. Is the dialer normally built into the voice platform, or do people usually connect separate tool together? Also curious how these setups handle scaling before things start getting messy.

If anyone ha worked with a real setup, I'd love to hear how it was structured.

the failures that scare me are not the ones where the workflow crashes. those are obvious.

it's the partial success ones: it wrote the draft, skipped the approval note, used an old source, scheduled the wrong version, or marked the job done because one step returned ok.

i've started treating every automated content or ops flow as needing three outputs:

• what changed
• what was skipped
• what needs a human decision

that sounds boring, but it catches a lot of fake progress. if an agent cannot explain the skipped part, i don't really trust the completed part either.

curious how others handle this. do you log partial success as a failure, a warning, or just a normal run with notes?

I got interested in workflow automation in my last job, and I’ve now set up n8n on a virtual private server and am using it to host workflows for the full-stack project I’m building, as well as my personal website.

The project is an AI and automation enhanced business simulation, with the idea being to experiment with where I can use AI and automation to, well, enhance the system. The project is still in its infancy, and so far all I’ve done is automate my notion dev log to my website dev log, and automate the contact form on my site.

Automations I have in mind:

·       notifications for customers and merchant (it’s both sides of an ecom store)

·       things around orders being placed such as a calendar note, inventory updated

·       coordinating marketing development for ‘new’ products added to the system

·       sales analysis > email summary

·       eventual CRM integration

These are just ideas, and I know that automation should come as problem solving/time reducing than backbone project structure, but I haven’t got that far yet so I’m still just letting my mind run with it.

Anyway, I thought I’d post this as an introduction as I’ll be posting more automations as I build them.

If anyone has built anything similar, or has any suggestions, I’d be interested to hear.

I am trying to build a meeting pipeline that does most of the boring work for me. The dream is record, upload, get transcript, push action items to Todoist, publish a summary to Notion, email the attendee list. I am about halfway there.

Currently I use an n8n webhook to listen for new files in a folder, send them to a transcription service, and then format the result. The fragile part is the transcription step. Some APIs take forever, some have strict file limits, and some return summaries that are too generic to be useful.

I have been testing vomo ai as the transcription step for now. I upload through the web app, download the transcript and action items, and then format them into the next steps. There is no native API yet, so the upload and export steps are still manual glue.

What I can get running in one weekend is something like this. If you have glued transcription into an agent workflow I would love to hear whether you went local or cloud and how painful the handoff was.

I've been experimenting with AI automation over the last few months, and one thing surprised me.

Building the automation is often the easiest part. Understanding the client's workflow, handling edge cases, fixing unexpected issues, and maintaining everything takes much more time than I expected.

I'm curious how others here are handling this.

• Do you charge a one-time setup fee, a monthly retainer, or both?
• Do you ask clients to pay for APIs and software directly, or do you include those costs in your pricing?
• What's one pricing mistake you made early on that you'd never repeat?

I'd love to learn from people who are already working with AI automation clients.

Dripify costs money n my n8n workflow automation chain for automated LinkedIn messages was free. LinkedIn updated a frontend selector last Tuesday n my headless browser flow started throwing errors. I spent three hours fixing it before my first call.

The DIY automation community makes linkedin message automation look easy. Scrape leads. Enrich them. Fire off connection requests. Then u deploy it n LinkedIn changes their DOM structure. Or ur proxy IP gets flagged. Has anyone here maintained a DIY automation stack for more than six months?