Computer now works where support teams work, helping solve tickets faster

TL;DR

• Support teams waste too much time rebuilding context – 20 open tabs, cross-referencing logs, hunting for past solutions – before they can even start solving the problem.
• Computer, by DevRev, now lives and works inside every ticket: it investigates across every connected system, and hands you a full read on the problem with root cause, evidence, and next steps, within seconds.
• Computer proposes actions, waits for your sign-off, and knows when to say "a person needs to do this". The judgment stays with your talented team, the legwork and busywork is gone.
• Rather than gathering context, teams can now focus on evaluating – and the whole team works at the same quality bar, whether they joined five years ago or five days ago.

Rebuilding context – every time – is a time-killer

It's 9:14am. A customer ticket lands. Before you can do anything useful, you start opening tabs.

The customer's history is in the CRM. The logs are in Datadog. There's a related bug engineering is already chasing in Jira. And somewhere in a ticket from five months ago, or a half-remembered Slack thread, someone has already solved this exact thing. So you copy, you paste, you cross-reference, and you build up all the context you need.

Then, four hours later, you can finally resolve that customer query. In the meantime, 12 other tickets have landed…

Support teams should be solving, not searching

For most support teams, the day is not spent exercising judgment, using intelligence. It's legwork, busywork, wasted work. Hunting, gathering, reconstructing. It's slow. It’s repetitive. It adds cognitive load. It’s exhausting. And it’s demoralizing.

Plenty of AI tools have promised to take this kind of work off your plate. But most are bolted onto your ticketing platform, so they can only see what that platform knows. They'll summarize the ticket, draft a reply, and rephrase it for you. Useful, but it leaves the hard part untouched.

The thing that actually drains the day is connecting the dots, between the CRM, the error logs, the open product bug, the account's health, and more – and an AI tool that can only see one system, one perspective, can't connect the dots.

That's the gap we've closed with Computer.

Computer, now right there where you work

Computer, by DevRev, now lives exactly where support teams work. Open a ticket, click on the " icon, and Computer begins its investigation. It goes straight to the part that needs a human: the judgment.

Computer unifies, organizes, and understands all your company’s live data – into what no other AI offers: Native Shared Memory. That’s your real business data, connected across every system, so the context is always precise enough to act on. It isn't reasoning from a single system or tool. It's reasoning across your entire company.

Here's what that changes.

It starts with a click

Open a ticket, and ask Computer to investigate it. A few seconds later, you get a full read on the problem, not just a quick summary. Computer lays out the customer’s problem, including how urgent it is, and how the customer seems to be feeling. It gives you the root cause, with the evidence behind it: the logs it checked, the filters it ran, and the past tickets that match. When Computer is certain, it says so. When something is still a guess, it says that too (and tells you what it would need to confirm it). It proposes a solution. And it gives you a clear set of next steps to close the ticket.

A plan of action, ready for you to approve

Computer can take real, decisive action: Post an internal note with its findings. Draft a reply to the customer. Update fields in the CRM. Change a ticket's status in another system.

But it never moves on its own. It shows you the plan first, and asks for your one-click approval. If the plan isn't quite right, just tell Computer what to change and it revises.

And when Computer can't do something, it tells you, instead of lying, pretending it already did it. If Computer doesn’t have the right permissions to take an action which can only be done manually, it says so and flags it. An AI that knows when to say "not me, a person needs to do this" is a feature, not a limitation.

Skip the catch-up, love the back-up

Some tickets can't be closed by one person. Sometimes a refund needs finance, a bug needs engineering, an at-risk customer needs the account manager.

Until now, looping someone in meant re-explaining everything. You write a summary, paste the logs, recount what you've already tried. The context you spent twenty minutes building gets compressed during handoff. Then the teammate opens their own tabs to verify it all anyway, and the back-and-forth begins.

With Computer, you pull a teammate into the same shared chat, thanks to “multiplayer mode”. They see the full context Computer has already built, so nobody explains the ticket from scratch. Two people work the same problem against the same evidence, with Computer right there to pull a log or check a record the moment either of you asks. The handoff stops being a reset.

Not every ticket is a bug

Some tickets are feature requests, and Computer handles those differently. Because it understands the category of problem & then suggests next steps accordingly.

Ask it to triage one, and instead of a root cause it gives you the use case: what the customer is trying to do, and why it matters to them. It tells you whether the capability already exists, or sits somewhere on the roadmap. It suggests how to respond. And it lays out the next steps, like linking the ticket to the right roadmap item, so the request reaches the people who decide what gets built.

What this all adds up to

When Computer does the gathering and rebuilding of context, support teams can spend their time on judgment instead of admin. They reply faster, with more confidence, and with the same quality, whether they joined five years ago or five days ago.

The average handling time on every ticket gets quicker. And support agents can handle multiple tickets at the same time, because Computer is handling the grunt work on each of them, all at once. Across a full queue, that adds up – fast.

The skills that matters shifts too. It's no longer about who can read a Datadog log, or trace a Jira bug. It's about evaluating well-evidenced context – instead of building it from scratch. Everyone gets to see the full picture of a customer's problem, even the parts they were never trained to read.

Why Computer beats all those AI solutions

Three reasons, and they all come back to one idea: Native Shared Memory.

Shared memory means Computer keeps one connected picture of your data, in one place, linked together, instead of scattered tools that don't talk to each other. Computer reads from that one picture every time. That single idea is what makes everything else work.

• Precise answers – because Computer isn't guessing, based on access to a single tool or system. It reasons over the full context, so what it tells you is grounded in real data, not a summary of what’s in front of it.
• Safe actions – because Computer can see the whole situation before it proposes a step, and still waits for your approval before it moves.
• Efficiency – because the context is built once and reused. The language model doesn't rebuild the picture from scratch on every query. That's how teams run the same model on Computer using up to 95% fewer tokens.

This is the Computer your teams already know, now sitting exactly where the work happens.

Get ready to be wow’ed…

The fastest way to understand all this? Watch it happen.

Book a demo and our talented team will show you how Computer handles a live ticket, from start to finish. Prepare to be (very) impressed.