since everyone's asking, let's talk AI :)
last week, I shared an update on everything Inrō has shipped over the last 20 months in automation, CRM, and integrations.
today I am doing a final update on the bigger shift coming this Saturday 25th: Inrō is now an AI-first platform, and here's what that actually means.
Because here's what we kept hearing: people would build a solid flow, it would convert, and then ask "can it just handle the whole conversation?" Not just send a message, but actually understand what someone wants, respond, collect info, route them, and follow up. So, we built exactly that.
A complete AI Agent for Instagram understands how you talk, mirrors your tone, knows your goals, taps into your knowledge base, collects information mid-conversation, takes actions, and escalates when a human needs to step in.
Not a chatbot. It handles the full conversation end-to-end.
But what if you want it more controlled?
AI actions built into every automation and campaign
AI questions: Understands intent, routes down the right path, no keyword matching needed
AI collect info: Extracts names, emails, budgets, dates and saves them to the contact profile automatically
AI condition branches: Splits flows based on saved data, tags, or previous answers
Full AI agent handover: Passes the conversation to your AI with a goal, it handles the back and forth, then returns control
AI agent message: Reads full conversation history, sends a contextual reply, automation continues
Build by describing: Just type what you want. Inrō builds the flow for you.
The quieter stuff that makes it actually behave - intent-based triggers that fire on what someone means not what they type, folder exclusions so the AI never touches conversations you want to handle manually, spam and hate detection, and automatic opt-out handling.
None of it needs configuration, it all runs quietly in the background so your flows just work without you having to babysit them.
MCP for Claude and ChatGPT Connect Inrō to the AI you already use. Query contacts, pull insights, manage everything in plain language, no code needed.
Everything goes live this Saturday April 25 along with discounts, surprises, and the full picture.
If you've been curious, that's the day to jump in and try it out!
Two questions now for you guys:
what's the first thing you'd want the AI to handle for you on Instagram?
and is there anything you'd want it to do that we haven't mentioned yet? 👀
Here was the launch -
https://www.producthunt.com/products/inro/launches/inro-ai
Replies
If a human jumps in mid conversation, does AI fully step back or still influence follow ups later?
Inrō
@paige_lauren1 We have made it so that it's completely as per your preference.
You can set it to fully step back the moment a human jumps in, no further AI involvement unless you manually re-enable it. Or you can configure it to stay quiet for a set period and then pick back up with a follow-up if the conversation goes cold again. The wait time, the number of follow-ups, and what happens after are all configurable.
@kshitij11 Good flexibility. Curious how you prevent AI from "double-following" while a human thread is still contextually active but just slow to respond?
Inrō
How well does the intent detection hold up with messy, slang heavy Instagram DMs?
Inrō
@oliver_nathan2
It's context-aware, so it's reading the full DM history, not just the single message. It knows what post or story triggered the conversation, so it already has context before the first word is typed. And it's been trained on real Instagram conversations, slang, abbreviations, typos included.
On top of that, you can manually add word variations yourself. So it's looking for those specific terms plus common variations, combined with the underlying message intent. It's not relying on any single signal.
Is it perfect with every possible variation of "lol hm tho"? Not 100%. But it handles the vast majority of real-world Instagram conversations a lot better than keyword matching ever did 😄
@kshitij11 Makes sense. Curious how it behaves when context is noisy across multiple overlapping conversations in the same inbox.
Inrō
The shift here feels less like automation and more like delegating conversations ownership, which is a bigger leap.
Inrō
@miles_anthony2
That's exactly the right way to put it, and honestly, a better framing than we've used ourselves.
Automation implies a rigid system doing a task. Delegation implies trust, judgment, and the ability to handle the unexpected. That's what we've been building towards, an AI you can actually hand something off to and not have to check on every five minutes.
The leap is real though. It requires the AI to earn that trust, which is why visibility, controls, and handback mechanics matter so much. You wouldn't delegate to a person you couldn't oversee or course-correct. Same principle here.
Saturday shows what that looks like in practice 👀
@kshitij11 Makes sense. In practice though, what's the fail-safe when delegation starts producing unintended actions at scale. Do you constrain behavior upfront or rely more on post action correction loops?
Inrō
@miles_anthony2 Primarily constraint-first, correction is a fallback not the plan.
Upfront you define exactly what the AI is trying to achieve, and equally importantly, what it's never allowed to do. Hard rules it cannot override regardless of the conversation. You control which contacts it can touch, which folders are off limits, and how many times it can follow up before stopping completely.
At scale the global controls kick in too. Opt-out detection, spam filters, scenario priority groups that prevent multiple flows from conflicting, all running automatically across every conversation.
The correction layer exists too though. Every action is logged, you have full visibility per contact, and you can step in and override at any point. But the goal is that by the time something reaches you, the upfront constraints have already handled 95% of the edge cases.
The honest answer is no AI system is perfect at scale, which is why we've invested heavily in making the constraint layer as granular as possible rather than relying on catching mistakes after the fact.
Premarket Bell
I like the idea of AI taking over conversations, but control still matters a lot. The handover model you described feels like a good balance between automation and oversight.
Inrō
@daniel_henry4 100% agree, and honestly that balance is something we've been very deliberate about.
The way we've built it, you're always in control of when the AI takes over, for how long, at what steps and what it's allowed to do. It's not a black box that runs loose. You define the goal, the boundaries, the handback conditions. And the moment a human steps in manually, the AI steps out automatically.
The vision is less "AI replaces you" and more "AI handles the parts you don't need to be in, so you can focus on the ones that matter." Saturday will show a lot more of what that looks like in practice 👀
Inrō
@daniel_henry4 Also, there are various mechanisms, such as excluding specific intents or entire folders/segments of your audience for AI.
This is a popular use case, in fact. People usually create a folder for friends/family and then add them to an exclusion segment to prevent AI from running on them.
Or there are intents like brand deals, sometimes for creators, etc.
The build by describing part sounds promising, but I’m curious how accurate it is in practice. Translating vague instructions into solid flows is harder than it sounds.
Inrō
@yahya_rogers Sharp observation, and you're right, it's genuinely one of the harder problems to crack.
The way we solved it is two-fold.
First, the AI doesn't just know what blocks exist, it understands the best combinations to reach a specific goal, trained on thousands of real templates across different use cases and industries. So it's not guessing structure, it's drawing from what actually works from what we built before.
Second, and this is something we're launching very soon, you'll be able to edit the generated flow using AI too. So if the draft isn't quite right, you just describe the change you want and it adjusts. The goal is that you never have to touch a block manually unless you want to soon and speed up the best setups.
Don't forget to try it on 25th if you wanna see it in action :)
I’d want strong visibility into what the AI is doing behind the scenes. Autonomy is great, but trust comes from being able to review and step in easily.
Inrō
@alicia_klein Completely valid, and it's something we've built for deliberately.
Every message the AI sends is logged and visible in the contact's history. You can see exactly what it said, when it said it, and why the flow went the way it did. Per-step metrics on every node show you sent, read, replied, and converted at each stage. So it's never a black box.
On the control side, you define exactly when the AI activates, which contacts it can touch, which folders are off limits, and the moment you step in manually, it steps out automatically. You're never fighting it for control.
Trust has to be earned through transparency, not just promised. That's been the design principle from the start.
Do you think there's other missing angles to focus on as well?
This feels like where Instagram automation should’ve gone a long time ago.
Sending auto replies is easy. Understanding intent, collecting lead info, and knowing when to hand over to a human is the real challenge.
Biggest use case for me: qualifying inbound leads automatically so I only spend time on high-intent conversations.
Curious how well it adapts to different brand tones and niches.
Inrō
@combajt Qualifying inbound leads automatically is honestly one of the most common reasons people come to us, and exactly the use case the AI Agent was built for.
On the tone and niche question, it adapts pretty deeply. It learns from your actual sent messages and comments so it picks up your natural voice without you having to describe it.
You can define its goals and shape the flow to match your specific funnel.
And you can feed it everything about your brand, your website, products, pricing, FAQs, all of it, so it's not just sounding like you, it actually knows what you know.
The result is less "this feels like a bot" and more "this feels like a well-briefed version of me." Genuinely think you should try it Saturday and see how it holds up for your specific niche :)