Another round of image edits
When a campaign changes, designers reopen, edit and export every asset one by one.
Start with one job your team repeats every day. It understands the goal, remembers the business, calls specialist skills, works in real software, and returns an outcome people can review.
The best entry point for AI is often not a grand transformation plan. It is the sentence teams repeat every day: ‘We have to do this all over again.’
When a campaign changes, designers reopen, edit and export every asset one by one.
Submissions, revisions and decisions live in threads, forcing operators to search, download and check repeatedly.
Several platforms and spreadsheets must be reconciled and copied into the same report every time.
These results come from project-owner descriptions. We preserve scope, human review and measurement caveats rather than presenting one outcome as a universal promise.
A user submits an asset package and instructions. The AI employee edits the batch, then a designer reviews the result.
BEFOREPreviously, each file was opened, changed and exported by hand; similar work often took half a day or a full day.
DELIVEREDAI interprets the request, processes the batch and returns the files. The designer decides whether they are ready to publish.
Actual time varies with asset count, complexity and review requirements. This is not a universal SLA for image work.
A workflow platform organizes submissions and status. AI applies company rules for first-pass screening; operators make the final decision.
BEFOREMaterials and acceptance records were scattered across chats, requiring repeated search, download and manual checking.
DELIVEREDA submission platform and AI screening route questions, exceptions and acceptance decisions back to operators.
The measurement period and scope remain to be documented. It refers only to repetitive work in this project—not headcount or total cost.
Enterprises do not need more AI tools. They need an action brain that turns intent into outcomes.
A general AI employee combines a persistent identity, executive brain, partitioned memory, enterprise policy, Skill Packs, applications and execution resources. People see one employee with many abilities; underneath is a versioned, isolated system that loads only what each task needs.
The employee is not tied to one app or one machine. Its executive brain understands goals, Skill Packs provide expertise, and governed tools complete the work.
A digital employee the enterprise owns and manages, with a role, schedule, goals, permissions and long-term memory. It is not a Windows machine or a platform account.
Understands enterprise goals, prioritizes work across skills, selects tools and accounts, evaluates risk, and verifies every outcome.
Candidate conversations, resume collection, support Q&A and after-sales workflows are independently versioned and loaded per task.
The brain routes tasks to visual desktop automation, a governed browser or an official API. BOSS, Liepin, WeChat and ERP are tools—not employees.
The brain never tosses a task to a script and looks away. After every atomic action the runtime observes again and verifies; anomalies, risk signals or human input immediately alter the next step.
Read screens, pages, messages, files and system events.
Turn raw signals into contextual business facts.
Use goals, rules, quotas and risk to select the next step.
Call an authorized tool for one minimal atomic action.
Use post-action evidence to confirm the outcome.
Record, recover or hand off, then decide again.
We do not assume every problem needs an agent or a platform. We first understand the work, then choose the shortest reliable path.
Structure the repeatable steps, then combine AI, rules and tools behind one clear task entry point.
Organize materials, status and collaboration first, then embed AI where it fits while people retain final judgment.
See how work happens and map inputs, tools, rules and bottlenecks.
Compare frequency, time, rule clarity and exception rates.
Compare against human outcomes and record where judgment must remain human.
Connect existing tools or add the missing workflow layer, with clear permissions and handoff.
Measure total processing and review time, rework and exceptions before expanding.
Evaluation includes human review time—not only how long the AI ran.
Start from real users and work samples to define the process, rules, inputs, outcomes and acceptance criteria.
Connect existing systems and add the workflow layer that gives materials, status and collaboration a clear home.
Combine task understanding, specialist skills and tool execution, returning reviewable outcomes and handing exceptions to people.
Product knowledge, brand rules and service standards stay governed at headquarters, while language, culture, channels and local policy load per market. Global operations do not need a fleet of disconnected bots—one AI employee can gain worldwide capabilities.
Unify overseas channels, customer feedback and competitor signals into traceable market opportunities and recommended actions.
More than literal translation: adapt content to brand voice, product truth and local expression, with review built in.
Connect DTC sites, marketplaces, social, email and CRM to handle leads, questions and after-sales coordination.
Global events enter one task queue. AI handles bounded work first and hands judgment calls to the right regional team.
Language, culture and regulatory boundaries are configured per market; local people retain review and control over publishing, commitments, refunds and other high-risk actions.
A Skill Pack defines the work to be done; applications are tools. The same AI employee can serve domestic teams or load language, channel and local-policy context for global expansion.
High-risk actions require human approval. Captchas, risk controls and anomalies are never bypassed automatically.
Understands the role, handles unread messages, collects resumes, searches candidates and reports results—continuously, inside quota, schedule and handoff boundaries.
Uses one governed product knowledge base to serve multiple languages, time zones and channels; refunds, complaints and local sensitivities go to regional teams.
Collects information, enters data and tracks status across browsers, files, Office and business systems, turning repetition into reusable Skill Packs.
The cloud control plane manages enterprises, employees, skills, tasks, entitlements and audit. Execution can run on customer premises or governed compute sites, connected outbound without exposing enterprise desktops to the public internet.
Tell us who does the work, how it happens, where time is lost, and which decisions must remain human. Together we will define the first entry point, execution boundaries and verifiable success criteria.