What makes Hop different
Proactive, not reactive
Every other AI assistant for work runs the same way round: you ask, it answers. Hop starts from your conversations instead. It reads your email and your Slack or Teams channels, works out what you’re actually in the middle of, and puts that in front of you with the next step attached: draft the follow-up you said you’d send, prep me for this afternoon’s call, chase the answer nobody gave you on Tuesday.
You’re still the one deciding. The difference is that the decision is whether to press the thing, rather than whether it’s worth stopping to write out a request in the first place.
An assistant waits for instructions. Hop tells you what needs your attention, which is closer to how a teammate behaves.
Today
In 2 hours · 1:00 – 1:30 PM
CloudRelay renewal call
Smart model routing
Hop routes between open-source and frontier models automatically. Simple tasks go to cheap models, hard reasoning goes to frontier ones. You never pick. Hop does, per task, weighing quality against cost.
For teams watching their AI spend, this means you’re not paying frontier prices for every email summary. You’re getting the right intelligence at the right price, automatically.
Routed to an open model
White-glove implementation
In our experience the tool is the small part of an AI rollout. Most of the work is setup, integration and tuning, and that’s the part teams run out of time for.
So it’s included. We sit with your team, connect your tools, configure the workflows and keep tuning them after launch, rather than handing over a login and a docs link.
That holds whether you’re a team of four or four hundred. There’s no size limit and no seat minimum, and small teams tend to get the most out of it, because there’s nobody spare to run the rollout.
That work has a name: Hop Advisory.
We connect your tools. We do, not a docs link
Workflows configured around how your team already works
Tuned until it earns its place, not just until it’s live
What Hop does for each team
The same proactive assistant, pointed at whatever your team is measured on.
Sales
What a deal is really doing shows up in the thread well before it shows up in the CRM. Hop reads the email and the channel, notices the one you said you’d come back to on Friday, and hands you the follow-up already drafted.
Hop for sales teams, in full →
Customer support
The customer still waiting on an answer somebody promised in a thread three days ago, usually the ones that never became a ticket at all. Hop reads the inbox and the escalation channel, and Zendesk gives it the history.
Engineering
Blockers get raised in a channel long before they reach a sprint board. Hop catches the question nobody answered and the review nobody picked up, and hands you the summary with the next action on it.
Operations
Approvals and chasing live in email and chat, which is why they’re invisible to most tools. Hop watches them, works out what’s waiting on you and what’s waiting on somebody else, and drafts the chase.
Integrations that actually work
Hop works with the email and communication tools your team already uses, so what it surfaces is grounded in your context rather than a generic guess. New integrations are added every week.
Why teams choose Hop over other AI assistants
Hop vs. ChatGPT
ChatGPT waits for you to describe what you need, which means you have to notice it first. Hop reads your email and Slack, works out what you’re on, and brings you the work with the action attached.
Hop vs. Claude
Claude is excellent at reasoning and writing, and I use it a lot. It still waits for you to start it, so you have to notice the work and prompt it before anything happens. Hop starts from the conversation you were already having.
Hop vs. agent builders
You describe a workflow, they run it. That’s genuinely useful, and Hop does it too. The difference is that it isn’t the starting point. Hop reads your communications from day one, so you get something before you’ve built anything.
More on why the category moved this way: what proactive AI actually means. Want your team fluent in AI as well as equipped with it? See Hop’s AI upskilling platform.
AI assistant for work: common questions
- What is an AI assistant for work?
- An AI assistant for work is software that handles work tasks on your behalf: drafting replies, preparing you for meetings, pulling context out of the tools your company runs on. Most are reactive: you describe what you need and they answer. A proactive one reads your email and chat, works out what you are in the middle of, and offers the next step without being asked.
- How is it different from ChatGPT or Claude?
- ChatGPT and Claude are excellent, and they only know what you put in front of them, which means you have to notice the work before they can help with it. Hop starts from the conversation you were already having. It reads your inbox and your channels and brings you the task with the action attached.
- Does it act without asking me?
- No. Hop proposes and you approve. You see the draft before it sends and the field change before it is written. That holds for every integration, because an assistant with access to a company inbox should not be able to act unsupervised.
- Which AI model does Hop use?
- Whichever the task is worth. Hop routes each task between open models and frontier models automatically, in under a second: routine drafting and summarising go to cheaper open models, hard reasoning goes to a frontier one. You never pick, and you are not locked to a single vendor’s roadmap.
- What tools does it connect to?
- Your communication tools, where the work actually gets discussed, and your systems of record, where the context behind it lives. The communication side matters most, because that is where the tasks Hop surfaces come up in the first place. New integrations are added every week.
- How long does it take to get running?
- You can start now and set it up yourself: connect your tools and Hop begins reading what is already there. Or sign up for advisory and we will book a call, walk you through it, connect your tools with you, build the first workflows with your team and keep tuning them after launch.
Keep reading
AI assistant for small business
Why AI stalls at small companies, and what it takes to make it stick without an IT team.
Read it →Best AI assistant for work
Nine tools reviewed on what they do, what they cost and where they fall short.
Read it →Proactive AI assistant
What makes an assistant proactive, and how it differs from one that waits to be asked.
Read it →Get started with Hop.
It takes one conversation.
We’ll connect your tools, configure workflows for your team’s needs, and have your proactive AI assistant running within days, not weeks of trial and error.
Prefer the short version? See what the product does.