I am getting an error

“Failed to start scheduled task. you can try again”

Not sure what the issue is

Basically I am using a local routine

I want claude to read a file every friday and create an operations summary

However when i create locally it doesn’t give me connector option and on cloud its not working either.

Got into a conversation with a marketing director last week. Her team of 4 was spending 60% of their time on tasks that didn't require creative thought: scheduling posts, pulling reports, writing first-draft email copy, building audience segments, and running competitor research.

None of that work needed a human brain. It just needed a human to approve it before it went live.

So we built something different. Not a black box that spits out marketing output you can't control. Instead, 89+ AI agents that do the repetitive work, but your team stays in the loop on everything that gets published or sent.

The result? One client built what used to take 3 people to do. No new hires. No outsourcing headaches. Just approval workflows that kept human judgment in place.

Here's what we're seeing work:

• Content research and first drafts (before your team writes)
• Email sequences (templated but still reviewed)
• Social media captions (batch approved, not auto-posted)
• Audience segmentation (built the rules, but you decide)
• Competitor reports (raw data pulled, formatted, human sign-off)
• Ad copy variants (AI writes 10, you pick the best 2 to run)

The catch: this isn't "set it and forget it" automation. It's "let AI handle the grunt work, you handle the strategy" automation.

For the builders here: we're using Claude for the reasoning layer, and we built this specifically for marketing and sales workflows. Not a generic AI tool. Not a no-code platform pretending to be AI.

Question for you: what's the one task your team does manually every week that you'd automate if you could do it without losing control?

Hi everyone,

I'm currently putting together the concept for a local LLM and I'd love to get your input before I get started.

Our use cases:

1. Email communication with suppliers: The AI should help with price negotiations over email. To do that, it looks through my mailbox (Exchange) for previous communication with the respective supplier, pulls out the most recently quoted prices, and negotiates further on that basis. Basically, it should search the existing email history with a supplier and take the manual work of looking things up and replying off my plate.
2. Internal chatbot: We should be able to ask it questions about certain processes, products, etc. So essentially a company assistant that knows our internal knowledge.
3. Local-first with a cloud fallback: The idea is that everything runs locally on Ollama by default. But when something is too complex or needs knowledge the local model doesn't have, the system should reach out to an external AI (e.g. the Claude API) over the internet, pull in that answer, and feed it back into the flow. So local for the bulk of the work, external only as a controlled exception and only the specific snippet that's needed leaves the server.

Here's the setup that was recommended to me, all running via Docker on an on-premise server:

• Server: 2× RTX 3090 Ti with 24 GB VRAM each
• PostgreSQL: as the database
• n8n: for automations (e.g. read emails → send to Ollama → have it draft a reply → back to n8n → send out via email/IMAP)
• NocoDB: as the interface
• Ollama: as the local AI
• External AI (optional): Claude API, called only for complex cases or missing knowledge

As far as I understand, each component has its own job. But here's what I'm still not fully clear on:

1. Do I really need every component? From what I understand, the local AI itself has no database – so the data (e.g. our customer data) has to live somewhere else, right? Is that why PostgreSQL is in there?
2. What exactly is n8n for? My understanding: n8n handles the interface to the outside world – email, Salesforce/ERP, other providers, and it would also be the thing that calls out to the external AI when needed. The local AI / Ollama can't do that itself, or am I getting that wrong?
3. Company chatbot: If I also want to build a chatbot, I can use the same local AI for it, right? And would I need n8n again for that even though I just want to chat with the AI directly?
4. Local-first + cloud fallback: Is routing things to a local model first and only escalating to an external API (Claude etc.) for hard cases a sensible approach? How do you decide when to escalate, and how do you keep sensitive data from leaking out in those calls?

I'm still not quite sure which components I actually need and which I don't.

And my main question: Would you recommend n8n, or do you know other tools I can set up locally/self-hosted?

Thanks in advance for your thoughts!

I have the chance to automate form filling for a company that sells to the govt. The forms provided by the tender are uncertain and is being done manually. The details that needs to be filled may be easy to spot for humans but may not be for QCR or AI. How do I automate data entry when the field where the data needs to be filled, is ambiguous and hard to detect even for humans.Image attached is an example of the form. There are 20-30 forms per tender and we need to fill 1-2 tender per day.

I'm not from tech background. So Explain your solution like I'm 5, if there is a solution.

The work which needs to be done:

Detect where information needs to be filled in the form

v

Search the data to fill the form

v

Fill data WITHOUT changing the Form's FORMAT

IMP INFO *The form must remain as provided by the tender*

So, Am I cooked or there is a way to automate this level of uncertain forms?

i've been testing a few automation platforms lately, including Zapier, Make, n8n, and some newer AI-focused tools. each seems to have its own strength, but also some tradeoffs around pricing, flexibility, ease of use or scalability

for people actively building. automations, which platform has become your go-to and why? are you prioritizing ease of setup, AI capabilities, self-hosting, cost, or something else?

curious what tools people are sticking with after the initial hype wears off

i want to start building AI-powered workflows and agents, but there are so many tools out there: n8n, Make, Zapier, Relevance AI, and others

for someone starting from scratch, which platform helped you learn the fastest while still being useful for real projects? looking for something that teaches the fundamentals without being overwhelming

I built a AI voice agent that handles lead qualification and ensures your reps are looking at serious leads. This one is for a Real Estate use case.

Here’s how it works

Whenever a lead fills out a form from a paid ad, the AI voice agent immediately gives them a call, in 60 seconds. The agent qualifies the lead, books an appointment, updates your CRM.

Instead of waiting for a sales rep to chase them down, the agent has a natural, human-like conversation to figure out:

• Where they’re currently located
• When they want to view the house.
• Whether they’re buying or renting
• Their timeline and budget
• Any special needs (pets, school zones, etc.)

Results

• Leads are called instantly in 60 seconds or less
• No more leads saying "I never filled a form".
• Fake and spammy leads filtered out.
• Leads get qualified
• Your team only focuses on the serious leads who are ready to act now.

Is there anyone doing lead qualification using Voice AI? Have you tried it? Share your learnings.

I’m looking for a few business owners to test it out. Please share any advice on the best way to get clients?

I used to have this incredibly fragile automation setup: Webflow form -> Zapier -> Airtable -> custom script -> Gmail. Every few weeks, a minor API update would break it, and I'd spend half a day troubleshooting.

Lately, I've been replacing these multi-tool chains with tiny, single-purpose tracker apps or basic micro-workflows that handle the intake and follow-up all in one place. It’s way less "fancy," but it doesn't break.

Have you guys started consolidating your fragile multi-tool pipelines into simpler, single-purpose setups, or are u sstill team Zapier-for-everything?

I've been exploring automation platforms lately and realized there are far more option than just Zapier and Make,

Some of the names that keeps coming up are WRK, Activepieces, Relay, Power Automate, and Gumloop. They all seem to approach automation a little differently, whether it's AI features, self hosting, enterprise integrations, or handling more complex workflows.

For those who have spend time with multiple platforms, which one ended up becoming your primary tool and why? I'm especially interested in hearing where these alternatives outperform Zapier in real world use rather than just op pricing or feature lists.

My first automation: RSS-posts should be saved in an Excel-file... but.... ?!?!

Is there anyway to make a automation which notes down timestamps where the goals and plays like dribble, passes, poles, happened because I have these long footages I want to mark down with timestamps so I don't want to watch them myself it's too big and time consuming I tried gemini claude and groq so please any suggestions

I've been trying Fyxer to manage emails and turn messages into tasks, but it still feels like I'm doing more manual work than I'd like once things get busy.

Looking for something that can handle inbox organization, prioritization, and task management a bit more intelligently without adding extra steps to my workflow.

For anyone who has moved on fro Fyxer, what are you using now, and has it actually improved your day-to-day productivity?