Computer-Use Agent Builds

Overview

What we deliver

We build computer-use agents that click, type, and navigate real applications to complete multi-step work without brittle scripts or API gaps.

Computer-use agents handle the work that lives between systems without public APIs. We design, build, and ship agents that operate browsers and desktop software the same way a trained employee would, following standard operating procedures and confirming each step against expected screens. Our team starts with a discovery review of the target workflow, then maps decisions, exception paths, and audit needs before any code is written. We use vision-grounded models and structured tool calls to keep behavior predictable, and we wrap every agent in observability so you can replay runs, inspect screenshots, and review reasoning. The result is a reliable digital worker that handles repetitive screen-based tasks while your team focuses on higher-value work. We deliver source code, runbooks, and monitoring dashboards so your operations group can run the agent in production with confidence.

Fit Check

Built for teams like yours

Who it's for

Operations leaders with legacy software
Finance teams running manual reconciliations
Customer service groups using multiple portals
RevOps teams stitching CRMs and quoting tools
Compliance teams handling repetitive filings

Pain points we solve

No API access to critical vendor portals
Hours lost to repetitive copy-paste work
Errors from manual data entry across systems
Backlogs in claims, billing, or reconciliation
Onboarding load for repeatable screen tasks

What's included

Capabilities

Everything we cover in this engagement.

Workflow discovery and process mapping
Browser agent development with Playwright and vision models
Desktop agent builds for Windows and macOS
Secure credential and session handling
Exception detection and human-in-the-loop handoffs
Run logging, replay, and screenshot capture
Production deployment on your cloud or ours
Maintenance playbooks and update routines

How we work

Our process

A clear, predictable path from kickoff to outcomes.

01

Discovery

We shadow the target workflow and document every screen, decision, and exception.

02

Design

We draft the agent architecture, tool calls, and guardrails before coding.

03

Build

We develop the agent in short sprints with weekly working demos.

04

Pilot

We run the agent in shadow mode against real work and tune for accuracy.

05

Launch

We deploy to production, train your team, and hand over runbooks and dashboards.

What you get

Deliverables & outcomes

What you get

Working computer-use agent in your environment
Source code and configuration files
Process maps and exception catalogs
Observability dashboard with run replays
Operator runbook and training session
Thirty-day post-launch support window

Outcomes you can expect

Reduced manual processing time on target workflow
Lower error rates on data entry tasks
Faster turnaround for backlog-prone work
Clearer audit trail for repetitive operations
Staff freed to focus on judgment-based work

Timeline

Six to ten weeks

Engagement

Monthly retainer, Project, Sprint

Tools we use

Anthropic Computer Use, Playwright, OpenAI Operator, Browserbase, LangSmith

KPIs we track

Tasks completed per hour, success rate, exception rate, mean handle time, cost per task

Client stories

What clients say

"

We were paying three agencies and a lifecycle freelancer to argue over attribution. RevoraOps absorbed all of it in 30 days, killed our worst-performing Meta ad sets, and rebuilt the welcome flow from scratch. CAC dropped 31 percent in the first full month. Honestly the relief of having one weekly call instead of four was worth it alone.

Megan W.

"

Our LCP was 4.8 seconds and Google was punishing us for it. They audited the build, dumped two plugins we did not need, moved hero images to a real CDN, and rewrote the critical CSS. LCP came down to 1.6 seconds within three weeks. Bounce rate on the pricing page dropped by a quarter without us touching the copy.

Sarah K.

Proof