The elevator pitch

• Most AI agents are bolted onto your support stack. They look something up, answer, then forget everything.
• Customer Agent runs inside the native Shared Memory built by Computer – so it knows what your entire company knows.
• It reads your knowledge, logs, sessions, and even the customer’s own screen – then takes action: refunding, changing account details, writing-back to SORs. Always with private data kept private.
• Computer builds the agent for you from your own support history, and wider systems. And it keeps improving, every week – reviewing real conversations, analyzing fixes, showing you the expected lift.
• BILL ran a proof of concept on 200,000 real queries. Customer Agent resolved 70%, drove more than $5M in savings, and held customer satisfaction steady.

“Nice to meet you”. “Nice to meet you”. Nice to meet you”.

Every morning, your current AI agent meets your customers for the first time. So if a customer gets in touch with a billing problem that your team already solved three times last quarter, your AI agent has no idea.

It pulls the customer record, gives a generic answer, and routes the rest to a human – who then re-reads the same history the agent couldn’t see.

Multiply that by every channel, every shift, every week. The AI agent never gets smarter. Because only your talented humans have a memory.

This is the quiet, but expensive tax most support teams are paying right now. Not because their AI can’t answer – almost every agent on the market can handle refunds, order status, booking changes. But because it can’t truly understand, remember, or learn.

This cost shows up in three places:

• Memory: Each AI agent is a brand-new island. Cut off from your team’s actual knowledge. Bolted onto support software that was already a mess of disconnected tools.
• Setup: You build it by hand, rule by rule, teaching it things your team already knows how to do.
• Improvement: That AI agent is exactly as good on day 365 as it was on day 1. Unless your team spends (i.e. wastes) time manually improving it.

What a customer-facing agent actually needs

Before you even get to the checklist of features, an AI agent worth deploying needs to do four things:

1. Resolve real issues end to end – not just answer, but act. And write back to your systems.
2. Work wherever your customers are – chat, email, social media, phone. Wherever they want to be, you need to be there.
3. Keep private data private – with every action logged, traceable, and reversible.
4. Get smarter over time – automatically, not manually. It should get sharper, and resolve more, every week you run it.

That fourth point is where almost every other agent on the market goes quiet.

Say “Nice to meet you” (once), to Customer Agent – by Computer

Customer Agent isn’t another standalone bot sitting next to your systems. It runs inside the shared memory of your entire organization – the same memory that powers your support team powers the agent facing your customers.

Computer, by DevRev, is the platform underneath. Customer Agent is what your customers experience.

Where other agents escalate, Customer Agent resolves

Most agents live on the first tier. They clear password resets, “where’s my order” questions, then escalate harder tickets. The ones that pile up – and up – because your team is so busy.

Customer Agent works on all-new levels.

When a customer says checkout keeps failing, it doesn’t stop at the FAQ: It reads the error logs in Datadog to see what broke. Pulls the order from Shopify to see the state it’s in. Walks through the customer’s live session. Reads the console output off their screen.

Customer Agent can do this because it works across all the systems your teams already run. A single conversation goes from spotting the bug to issuing the refund – without a handoff. And every action is safe, and contained: private data stays private; each step is logged, traceable, and reversible.

For the hardest issues, Customer Agent doesn’t work alone. It spins up a team of specialist agents: One digs through the logs. One traces the order. Another drafts the fix. They work in parallel, then come back with a resolution – the way a war room of engineers would, except it happens inside one conversation, and takes a fraction of the time.

Customer Agent arrives ready for work

Every other AI agent on the market is something you wire up by hand, maintain by hand, fix by hand. Computer’s Customer Agent is built – and looked after – by Computer.

Here’s how it works:

1. Computer unifies all your data and history. Months of tickets, conversations, and resolved chats. It finds the patterns, the questions that come up again and again. And the connections between siloed data and teams. And the gaps that need filling.
2. It drafts a working agent. It defines the steps for each workflow. Drafts the guardrails for what the agent should never do. Wires skills to the systems already connected in your workspace. Picks up the tone from how your team actually writes, and the languages your customers actually send.
3. You shape it. Review the draft, adjust what needs adjusting, approve when you’re ready.
4. It ships. Ready to work – and trust – from day one.

You don’t teach Customer Agent the basics. It arrives with skills for the jobs every support team runs – refunds, order tracking, password resets, subscription changes, account updates.

For industries like fintech, ecommerce, and banking, Computer starts from templates shaped by real large-scale deployments.

Your ecommerce Customer Agent knows how to handle a chargeback dispute.

Your fintech Customer Agent knows never to stray into unwarranted financial advice.

Your banking Customer Agent understands the difference between a pending hold and a posted charge – and explains it without jargon.

Instead of a blank canvas, you start with an agent that already speaks your industry, knows your brand, and understands your customers – then you shape it from there.

Fast answers? Deep reasoning? Your agent, your choice.

Most AI agents are rigid blackboxes. Customer Agent can be configured to run in two modes:

• Dash mode – built for speed and cost on high-volume, working with well-defined queries. The agent pattern-matches, retrieves, acts. As fast and affordable as it gets.
• Deep mode – for the hard stuff. The agent reasons across multiple systems, weighs conflicting signals, and works multi-step problems before responding. Slower, more thorough, higher accuracy on complex issues.

Set the mode yourself, or give Computer a value-and-cost target, so it can make a call per conversation. We benchmark new models as they ship, and keep each mode current – so you’re not re-tuning every time the field moves.

“Hello, how can I help you today?”

Customer Agent works across chat, email, and WhatsApp. We’ve also just launched voice capabilities – so your customers can dial in, and talk to the same agent, with the same memory, and the same ability to act and resolve in seconds, rather than leaving them on hold for hours.

If a call goes somewhere it can’t resolve, Computer Agent hands off to a human, along with full context. Learn more about Voice AI →

It gets smarter. And smarter. And…

Most agents are frozen the day they ship. Customer Agent grows – because Computer keeps working on it long after go-live.

Think of Computer as the teammate who constantly keeps an eye on your agent. Every week, it reviews the conversations – the ones the agent nailed and the ones where it fumbled. By Monday, it’s back with a short list of suggested improvements:

• The question customers kept asking, that never quite got a real answer – now answered every time.
• The reply that leaked something it shouldn’t have – now caught before it ever goes out.
• The phrasing that confused a customer mid-flow – now made as clear as possible.

Small but vital fixes – each earned from something a real customer actually experienced, and something that Computer proactively spotted.

You read the list over coffee. Approve what makes sense, reject what doesn’t, change anything you want. Nothing goes live without your explicit approval. And any changes or actions can be rolled back at the click of a button.

That compounding improvement never stops. The agent you launch on day 1 gets more and more valuable, day by day, month by month.

Real-world proof: BILL

BILL, the fintech platform behind payments and accounts payable for 500,000 small businesses, handles around 1.4 million support queries a year. Costs were climbing, ticket volumes were growing, and headcount couldn’t keep up.

Partnering with us, they ran a proof of concept on 200,000 real customer queries. The results knocked them sideways:

• 70% of queries automatically resolved by Customer Agent.
• $5M+ in annual savings.
• Customer satisfaction holding steady, or climbing – because precise, on-brand answers were delivered in seconds.

In production, Customer Agent became the first response across BILL’s product, web, and mobile. From authenticating users to creating and updating Salesforce cases – it escalated cleanly only when a question needed a human. All without disturbing Salesforce as the system of record.

Even better: full deployment across every customer segment took just 15 weeks.

As one leader at BILL put it: “Deflection only matters if it resolves the issue correctly.”

Pay for results, not seats

Customer Agent is consumption-based. The unit you pay for is a support conversation: one full session where the agent handles a customer’s inquiry on its own, start to finish.

Billing questions, subscription changes, password resets, login trouble – each conversation costs a set number of credits, so your bill tracks the work the agent actually does.

No per-seat licensing. No risk of unused licenses gathering dust.

See all pricing →

Simple resolution = table stakes

Every AI vendor is offering that lower-tier resolution. The two questions that matter now, and that will become more urgent (very quickly):

1. Does your agent truly understand, and remember, your business?

2. Does it keep getting smarter every day, making it more and more valuable?

That’s real agentic customer support – the kind we’ve built, and the kind we’ll never stop improving.

Your team handles what needs a human.

Customer Agent handles everything else – and turns up sharper every morning.

The gap between “AI-deflected” and “AI-resolved” is closing fast. The gap between an agent that knows your business and one that doesn’t? That’s only going to get wider the longer you wait around.

Our own friendly humans are ready to show you what Customer Agent looks like. So what are you waiting for: book a demo.