Real businesses asking for AI automation and workflow help on Reddit right now, updated every week.
Businesses drowning in manual work don't search directories for AI consultants - they ask Reddit. Posts like "How do I automate my lead follow-up?", "Can AI handle our invoice processing?" and "Looking for someone to build an n8n workflow" appear daily across r/smallbusiness, r/automation, r/Entrepreneur and niche operator communities.
Below is a live sample of those posts, discovered by Leadverse and filtered for clear buying intent: people describing a concrete process they want automated or explicitly asking to hire AI automation help. The list rotates weekly as new buyers surface.
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Live ai automation & consulting leads from Reddit
Anonymized previews - the full posts, links and outreach drafts are inside Leadverse.
What tools help organisations meet AI audit and documentation requirements under emerging regulation?
i handle a chunk of our compliance work and the documentation side i mostly have covered. so model inventory and policies live in our grc stack... and map to iso 42001 and nist rmf well enough. but where i'm stuck is the evidence the frameworks expect you to produce about how the ai behaves under pressure. we operate across enough states that texas traiga is the one we have to comply with now. its safe harbor leans on adversarial testing and documented internal review... so testing-and-records is a big part of the defense if a violation ever gets alleged. nist rmf isn't binding on its own, but traiga names alignment with it as an affirmative defense...so it earns the same protection. iso 42001 wants evidence your controls run, including system evaluation.... not just a policy saying you would. eu ai act is heading the same way for our eu-facing stuff. so the gap isn't where i store documentation. it's how i generate adversarial-testing evidence credible and repeatable enough to put in front of an auditor or an ag. a one-off pentest doesn't cut it, because the rag assistant and the agent change every sprint and the evidence goes stale almost immediately. federal preemption could scramble the state picture, but the testing-and-evidence expectation runs through nist, iso, and eu regardless.... so i'd rather build for it now than guess. if you've stood up adversarial or red-team testing that produced audit-grade evidence for an ai system, what are you running and how does it feed your audit trail?
Need advice on GHL automations, good workflow, and AI agent
Recently switched from Active Campaign to High Level and I'm wrapping up the final details with the company helping with the transfer. I own a portrait studio and we do a lot of volume. I run Meta ads and get a significant amount of leads we just aren't closing. I know the AI and automations will help with the follow up and I won't be wasting money. I cringe when I think about the amount of money I waste on ad spend because of the lack of follow through. It's my fault too, I'm not an expert and I would like help on setting up a good system to follow up on 30-40 leads per day until they say no or die so I'm not wasting money. Any consultants here? Or anyone with an excellent track record on managing ads for a luxury brand that relies on in person customers? I need advice from both so i can set up GHL perfectly for success along with a great AI agent.
Looking for someone in Pakistan who loves automating workflows/building internal tools — where do I find such people from GIKI?
A GIKI alumnus this side. Looking for someone who loves automating workflows/building internal tools I’m trying to find someone early-career who enjoys building systems and automating workflows. Not looking for a senior software engineer. More like someone who enjoys: building Airtable/Notion/internal tools automating repetitive work experimenting with AI tools connecting systems using APIs learning things like n8n, Python, etc. The work is around solving real operations problems in supply chain and logistics for a US based firm. Also open to connecting if someone has built projects like this.
how do I evaluate which managed automation tools are worth investing in to streamline our repetitive operational workflows without disrupting our current systems?
I keep running into the same bottleneck: my team spends hours every week on manual, repetitive tasks like data entry, scheduling, and follow-up emails that pull us away from higher-value work. I'm trying to figure out how to evaluate which managed automation tools actually fit our workflows, since I don't have the technical background to assess integration complexity or long-term maintenance needs myself. What worries me most is picking something that looks good on paper but ends up creating more work than it saves, or that doesn't scale as we grow. I'd like a clearer framework for weighing cost, ease of setup, and reliability before committing to any solution.
What’s the best way to find a robotic process automation services provider that actually understands our industry’s compliance requirements?
I keep running into the same wall when I look into robotic process automation services: most providers seem to lead with generic efficiency pitches instead of showing they've actually worked through the compliance headaches specific to industries like mine. I need to see real evidence that they understand the regulatory constraints around data handling, audit trails, and approval workflows before I'd trust them near our processes. It's hard to tell from a sales page or case study alone whether that expertise is genuine or just marketing language, so I'm not sure what to look for that would actually prove it out. At this point I'd rather find a way to vet that compliance depth upfront than get partway into a rollout and discover gaps.
AI for Customer Support: What tools are the best for SaaS/Full Stack?
We're a small SaaS team and support is starting to eat us alive. Same questions every day, high volume, nothing complex, just repetitive. I'm looking for AI tools for customer support and I want to get real opinions from people who're already using it Two things I'm trying to figure out: What are the best AI customer support tools that you can train on your own docs, help center articles, product documentation, internal SOPs, and have it reply directly to customers like a human would? We've looked at a few, the one we've tested most so far is Chatbase, trained it on our docs and pricing page in an afternoon, no dev needed, and it's been handling the repetitive stuff reasonably well. Are there good AI voice tools for support? Like an actual 1800 number where it's not a human on the other end but an AI that can hold a real conversation in real time. Do these exist at a level that's actually usable? Haven't found anything convincing yet. If there are any tools you've had good experiences with, please let me know. Really appreciate the help
Buenas, quiero armar una empresa no-humana de asesores financieros. Tengo todo lo necesario excepto el conocimiento de como armar el agente y hacerlo escalable Necesito un socio tecnico para armarlo, es un nicho a atacar y lo podemos hacer rapido, adaptandonos a los mil recovecos normativos y demas.
How do you all keep up with WhatsApp leads without letting any slip?
Solo agent here, and honestly the second I list something my WhatsApp just explodes, 40+ people all asking 'still available? or 'price?' or 'can I see it saturday?' at once, and since I'm out doing viewings all day I reply late and the serious ones have already gone quiet or booked with someone else..Feels like I'm losing real deals purely on response time..How do you all keep up?
I’ve built a SaaS platform for data analysis using AI. In theory, I’m ready to launch an MVP (a pretty big one), but I’m wondering if it’s worth doing—or if it might be better to live a comfortable life with a good salary working at a Fortune 500 company. I’m a solo founder with many years of experience in IT as a software engineer, and I’ve always wanted to try my hand at running my own business. But the closer I get to the release, the more I’m afraid of it. I think it would be different if I had support—if everything weren’t resting solely on my shoulders—which is why I’m looking for a co-founder or a company that would take over the project in exchange for an appropriate equity split. If anyone is interested, please let me know. Here are a few screenshots of my platform below
Looking for a technical co-founder / CTO (India) to lead API + SDK engineering — early-stage deep-tech AI startup
Early-stage deep-tech startup building AI infrastructure — we're turning our multi-modal ML models into a clean developer platform (API + SDK) that any app can plug into. Keeping the specifics off a public post; happy to go deeper over DM after a quick intro. We are looking for a technical co-founder / CTO to own the engineering side: architecting the API and SDK layer, cloud + edge deployment, and taking our models from research to production-grade, low-latency infra that developers actually enjoy using. The founding team has serious pedigree — a PhD with international recognition working in this exact domain, plus co-founders with backgrounds spanning MAANG and Big 4 (senior ML and enterprise engineering roles, shipping at scale). We'd want a CTO who brings comparable credibility: someone who's led engineering teams and built developer-facing APIs/SDKs or ML infrastructure, ideally with Big Tech or equivalent high-bar experience behind them. A few details: Based in India, ideally but flexible for the right candidate Must be available full-time and exclusively Pre-fundraise stage — equity-only for now, with a salary once we close our raise (same for all co-founders) This is a co-founder seat, not a job If that sounds like you, drop a comment or DM with a bit about what you've built.
Is inbound lead automation improving B2B SaaS conversion rates or just filtering out leads faster?
Right now our process is marketing, spends money, people fill out forms, then we play hot potato in the CRM while high intent buyers wait 12 hours for a reply because the routing rules broke again. Click to meeting conversion is all over the place, SDRs are doing manual triage in spreadsheets, and leadership keeps asking why inbound is not a magical AI SDR that prints pipeline. I am looking for AI powered lead engagement stuff and conversational marketing platforms that promise instant qualification, demo scheduling automation, and clean CRM integration. Has anyone gotten inbound lead automation to increase pipeline without building a second career as a RevOps admin, and if so what stack or approach worked for you?
What's your go to tool for cross functional deal collaboration?
this is my first time owning the full deal process across teams and i am realizing just how messy cross functional collaboration gets once the deal is not straightforward. Right now our setup looks something like this: 1. CRM for pipeline and basic notes 2. Slack channels spinning up for bigger deals 3. A shared drive for contracts and decks 4. Random spreadsheets for approvals because it is faster this way This kind of thing works until a deal hits that gray zone where product has to weigh in on roadmap, legal wants to adjust language, finance wants to change terms and cs wants to manage expectations. Then suddenly everyone is talking to the customer separately and i am stuck trying to piece it all together from different tools.
Welche Tools skalieren eigentlich noch gut für 'n wachsendes Startup? Unser aktuelles Setup bricht grad voll zusammen.
Wir sind in 'nem guten Jahr von 8 auf 42 Leute gewachsen, wir machen SaaS und anderen Tech-Kram, und die Nachfrage steigt einfach schneller als ich hinterherkommen kann. Einstellen ist natürlich das Erste was man tun muss und ich bin da eh schon dran, aber was mich eiskalt erwischt ist wie viel von unserem internen Setup klammheimlich den Geist aufgibt je mehr wir wachsen. Sachen die bei 10 Leuten noch völlig okay waren werden bei 42 zu 'nem echten Krampf. Einiges von dem was bei uns grad schon bricht: \-Shared Drives: Ordnerberechtigungen die geklappt haben als noch jeder jeden kannte fangen an zu viel zu teilen oder blockieren Leute. Wir integrieren grad schon Google Workspace aber ich würde mcih über Feedback zu seinem Skalierungspotenzial freuen \-Onboarding: jeder Neuzugang muss Konten manuell in voll vielen Apps einrichten, ich dachte da an Rippling für. \-Tool-Wildwuchs und überlappende Abos: jedes Team sucht sich seine eigene App aus, von denen sich voll viele überschneiden und keine redet mit der anderen. Würd Zapier helfen das einzudämmen? \-Passwort-Manager: im Moment liegen unsere Passwörter in Google Docs (so ein Doc pro Abteilung) und werden manchmal über Slack verschickt (ich weiß, ich weiß). Es fühlt sich weder sicher noch audit-freundlich an also dachte ich drüber nach Passwork dafür zu integrieren. Wir sind fast 50 Leute was der Punkt ist wo Audits wje NIS2 reinkicken also versuch ich echttt das ASAP dichtzumachen. Will mal sehen was ihr so nutzt und was eure Reviews/Meinungen zu alelm sind was ich geschrieben hab, danke.
Looking for an AI browser agent that can take over after I log in and complete hundreds of web forms
I’m looking for recommendations for an AI browser agent that can take over after I’ve logged into an authenticated web app and generate realistic test data by completing forms through the GUI. Importing directly into the database isn’t an option because of the complex workflows, JSON data, audit logs, and business logic, so everything needs to happen through the existing interface. Ideally it would understand the page like a human (rather than relying on brittle selectors), fill out forms with realistic data, navigate multi-step workflows, and run unattended for hundreds of submissions. Has anyone had success with tools like Browser Use, Stagehand, ChatGPT Agent, or something similar, especially one that can attach to an existing authenticated browser session?
I help run operations for a product org that's scaling fast. Product and engineering are 300+, sales is around the same size, and everyone's spread across multiple time zones. The problem is probably familiar. Feedback from the field (sales, CS, solutions) comes in constantly, but it's scattered across Slack, calls, one-off docs, and a spreadsheet nobody fully trusts. Product ends up with a pile of asks and no context to prioritize them, and when the roadmap shifts, the field feels like their input disappeared. Trust between the two sides takes the hit. I'm interested to learn about solutions that can scale, but feel simple. A few things I keep circling: What intake and routing setup genuinely worked for you? One front door, or per-team? Which tools were helpful? How do you close the loop back to the field so people know what happened to their input, without a human manually chasing every item? Do you have regular cadences with them? Or just send over reports? What broke specifically because of scale or time zones? Async handoffs, who owns triage, duplicate asks? Thanks for your insights!
What are the key benefits of using managed automation tools to streamline our business operations? How do we choose the right provider for our specific industry needs?
I've been looking into managed automation tools because I want to cut down on the manual, repetitive work that's eating up my team's time. What I'm most curious about is how much of the setup, monitoring, and maintenance is actually handled for me versus what I'd still need to manage in-house. I also want to understand the real cost-benefit tradeoff, since some solutions promise big efficiency gains but come with steep onboarding or subscription costs. Ultimately, I'm trying to figure out which option would scale well as my business grows without requiring a complete overhaul down the line.
Hi everyone, I’m building a new app for learning language. I will announce it soon. But here is the thing, i want to automate the marketing things with ai agents. Can i do that and if yes, how? What do you do for marketing? What are your suggesitons?
Alternative to Huly? Will consider paid options too.
really enjoyed huly, but the lack of mobile app and AI agents support is making me want to look else where. love how simple Huly is. Anyone considering switching away, and have suggestions?
Looking for an AI Workflow for Multi-Format Key Visual Adaptations
I work with a large creative team, and a significant portion of our time is spent adapting Key Visuals into multiple graphic formats. Each campaign Key Visual is typically adapted into at least eight different sizes. The messaging, imagery, and branding remain exactly the same, the only things that change are the canvas size, layout, and positioning of the elements. Today, our entire creative production workflow is built around Adobe applications (mainly Photoshop). I'm looking for a way to use AI to speed up this adaptation process. I've tested several workflows using Claude and ChatGPT. The results are promising (quality around 90%), but not reliable enough for production. We work with premium brands, so every asset must meet a very high quality standard before it can be published. Here are some of the approaches I've tested: 1. Uploading the original PSD file. 2. Uploading the Key Visual as a PNG. 3. Uploading the individual design assets as separate PNG files. Has anyone successfully built a workflow for this? I'm especially interested in: Workflows that preserve layout quality and visual hierarchy. Real production experiences rather than demos. Any recommendations or lessons learned would be greatly appreciated!
For those in payroll audit, or similar. Any shortcuts to autofill payroll pdf into excel
Doing payroll audits at my firm and we are uploading the payroll manually into our excel sheets. Im looking if anyone knows how expedite that and have it automated.
I’d like to hear references or best practices of how people build and expand their AI automation teams to build products that connect to actual systems, handle edge cases, etc. I am looking for folks that can do more than just type the problem statement to Claude.
Best AI cold calling tool for a small outbound teams?
I am running a four person outbound team in insurance field. I'm looking for an AI cold calling tool that can handle TCPA scrubbing and does not hallucinate on quotes. Most reviews are written by vendors themselves. What are you guys using right now?
simple CRM agent: Claude Code vs Hermes vs OpenClaw
I have a startup and I do outbound sales, but I have terrible memory, so I want to have some simple local agent where I can paste the memos of client meetings (or Linkedin chats) and it will do me reminders of when I need to followup with them on something. Also it would serve as my CRM of leads if I ever need to know something about a client. What is the best setup for this? I am using actively Claude Code, so it would be my default, but happy to also try Hermes or OpenClaw if they are better for this use case.
The Mission: Stop manual work. Build automations. Scale our Go-to-Market engine using code, APIs, and modern tools. What we’re looking for: • A fresher with great coding/logic fundamentals OR someone with startup experience. • Familiarity with APIs and integration logic. • A massive plus if you've touched tools like n8n, Zapier, Make, HubSpot, or Salesforce. • A problem-solver who wants to see their tech directly impact business growth. What you’ll get to do: Work at the intersection of Engineering and Revenue. You will own our automation workflows, integrate AI-powered tools, and collaborate across teams to build a frictionless growth engine. Location: Bengaluru
Looking to automate my billing operations with AI, is there any agents / tools that would be good for this? The sales team in my firm are closing deals with a ton of weird custom tiers nowadays so my Stripe setup hasn't been working. I'm sick of doing everything manually, so if there's any AI that can automate billing operations I'm extremely open to it. Thanks.
Best AI Solution Providers in India Right Now (2026)?
We’re currently evaluating vendors for an AI-led transformation project (mix of automation + some GenAI use cases), and honestly the market feels crowded. Everyone claims they do “end-to-end AI,” but in reality it seems like most either focus only on strategy or just execute without understanding the business side. Curious to hear from people who’ve actually worked with these firms: · Who are the best AI solution providers in India right now? · Any real experiences (good or bad)? · Is it better to go with consulting firm’s vs IT players?
How are you handling call notes and CRM updates after every meeting?
Reps on my team treat CRM hygiene as optional and I mean I get it, it's 20 minutes of soul-crushing data entry after every call. I want the notes, the fields, the next steps, the follow-up to basically happen on their own after a meeting, cleanly, without wrecking the CRM structure. What are you using in 2026 to automate the post-meeting CRM work that doesn't create a straight up nightmare?
Has anyone replaced forms with AI SDR/chat flows for high-intent B2B leads?
Quick context so this doesn’t sound like I’m trying to reinvent marketing on a Monday morning mid-size b2b saas (mid-5-figure acv). our high-intent visitors are getting slowed down by standard long forms and sdr response times. i want to test a formless, instant-scheduling funnel (click-to-meeting) for this segment using ai sdr software. Has anyone replaced forms with ai/instant qualification without messing up abm tracking or crm hygiene?
automation is supposed to save time, but maintaining tools is turning into a second job
dealing with a tedious workflow where i have to manually copy data from an old legacy database portal into excel.neither has api,and doing this everyday is an absolute productivity killer and a massive mental drain. everyone tells to just write script wrappers,but in reality, subtle layout shifts or session timeouts break the software level triggers. you end up spend more time debugging the automation tool than actually saving time. it completely defeats the whole purpose of trying to be efficient. it feels like standard software level automation is a dead end for routine office tasks. true productivity shouldn’t require you to maintain code or fix broken selectors. the execution loop should just be purely visual the machine looks at the interface exactly like a human does and handles it.until automation decouples from the software layer entirely like using local vision models paired with hardware inputs, we're just trading manual data entry for manual script maintenance.
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