Research and sourcing
Find accounts, candidates, vendors, companies, or topics from approved sources and return source-linked notes.
AI employees for business workflows
Gobii helps teams deploy AI employees as supervised AI teammates: persistent workers that browse, research, collect data, prepare outputs, and hand work back with sources and review points intact.
Definition
AI employees are software workers built for a defined business workflow. They do more than answer prompts. They use context, tools, browser access, files, and instructions to complete a series of steps.
At Gobii, we call them AI teammates because the work stays collaborative. The AI teammate handles repeatable execution. People set the goal, choose sources, review uncertain work, and decide what moves forward.
The AI employee knows the workflow, success criteria, tools, and output shape.
It can browse, compare sources, collect data, structure findings, and prepare handoffs.
People approve ambiguous decisions, sensitive actions, and outputs that affect customers.
The workflow can run again with better instructions and feedback from reviewers.
Capabilities
Teams use several names for this category: AI employees, an AI employee, AI workers, virtual AI employees, and AI teammates. The label matters less than the work. A useful system can own a clear workflow and show enough evidence for people to trust the result.
Find accounts, candidates, vendors, companies, or topics from approved sources and return source-linked notes.
Compare records against criteria, fill missing fields, flag uncertainty, and prepare review-ready tables.
Watch pages, feeds, directories, or public signals on a schedule and summarize meaningful changes.
Turn gathered context into briefs, outreach drafts, status updates, summaries, and next-step recommendations.
Package outputs for humans or downstream tools with source links, review status, and clear decision points.
Pause for approval when a workflow needs judgment, access, compliance review, or a decision that should stay with a person.
Workflow examples
When teams hire AI employees, the best starting point is work between existing tools. Think source-backed research, list enrichment, scheduled monitoring, and consistent handoffs.
Find accounts, inspect fit signals, prepare notes, and hand qualified leads to sellers for review.
AI sales agentCollect candidate context, compare role fit, summarize source links, and prepare a recruiter-reviewed shortlist.
Check approved pages, gather changes, flag exceptions, and prepare a concise update for the owner.
Turn audience notes, competitor pages, and source material into draft briefs that a marketer can edit.
Terminology
These terms overlap, but each highlights a different concern. AI employees describe the category. Gobii uses AI teammates in product language because supervised work depends on trust.
The commercial category: software workers with a workflow, tools, review points, and accountability for output.
The technical pattern: systems that can reason through steps and take tool actions to complete a task.
A broader label for automated labor. It can include workflow tools, agents, and role-specific digital workers.
Gobii's preferred product language: a collaborative AI employee that works under team supervision.
A human-friendly phrase for persistent collaborators, especially when the agent has identity, memory, and a regular cadence.
Choosing a model
These categories are different. Choose based on the workflow, tool access, supervision, and evidence your team needs.
| Decision point | Gobii AI teammates | Chatbots | Generic AI agents | AI employee marketplaces |
|---|---|---|---|---|
| Starting unit | A persistent teammate with a charter and recurring workflow | A conversation or prompt session | A technical capability built around a task | A prepackaged role selected from a catalog |
| Workflow ownership | Runs defined work over time and requests input when blocked | Usually responds inside the current exchange | Depends on the orchestration your team builds | Varies by the provider and selected role |
| Tools and context | Browser, files, apps, APIs, schedules, and persistent context | Typically chat plus a limited set of connected tools | Configurable by the team implementing the agent | Defined by the marketplace and role package |
| Supervision | Visible plans, input requests, approval points, and timeline activity | A person reviews the response after it appears | Approval and observability must be designed into the system | Controls vary across vendors and roles |
| Evidence and handoff | Source-linked outputs, known gaps, reviewer context, and structured handoffs | Primarily a conversational answer | Determined by the implementation | Determined by the role and provider |
| Best fit | Teams that want flexible, supervised AI workers around real workflows | Questions, drafting, and conversational assistance | Technical teams building custom orchestration | Buyers who want to select a packaged role quickly |
Gobii operating model
Use Gobii when an AI teammate must move through websites, documents, spreadsheets, and connected systems to reach a clear outcome. It does not replace a department. It handles the slow, repeatable work around the team.
That model fits AI employees for business teams that already know what good output looks like. Common users include RevOps, sales, recruiting, marketing, research, operations, and customer-facing teams.
Workflow brief, source lists, files, examples, tools, constraints, and output requirements.
Browse, inspect, extract, compare, summarize, draft, structure, and record what happened.
A human checks judgment calls, rejects poor matches, approves good work, and gives feedback.
Send reviewed output to a spreadsheet, CRM-ready import, document, message, webhook, or next task.
Deployment
Every useful AI employee needs clear controls. The team decides what the AI teammate can do, where it can look, how it reports uncertainty, and who approves the output.
Choose one repeatable workflow with known inputs, a useful output, and enough examples to show what good work looks like.
Limit sources, tools, credentials, cadence, data fields, approval gates, and actions that need explicit human permission.
Inspect sources, check fit, correct mistakes, and turn feedback into better workflow instructions for the next run.
Move approved work into the team's system of record with links, fields, reviewer notes, and a next action.
Governance in Gobii
Supervision is built into the workflow. Gobii keeps credentials out of chat and records the work. Teams can narrow access or stop an action before it runs.
Secret values are encrypted before storage and can stay scoped to one Gobii, a user, or an organization.
Native app capabilities reflect the connected account and granted OAuth scopes. Missing access stays unavailable until it is granted.
The timeline keeps messages, plans, tool activity, pending requests, generated files, and completed deliverables together.
A Gobii can pause for human input, a credential, contact permission, or approval before an important change or external action.
Disconnect an app or remove a stored secret when the workflow no longer needs it. Access can be narrowed without rebuilding the AI teammate.
Where to start
Start with valuable, repeatable work that is slow because people must collect or format information by hand. Choose a workflow with a human owner who can review the output and explain what to improve.
Compare Gobii starting pointsUse AI employees for prospect research, account monitoring, enrichment, CRM-ready prep, and sales handoffs.
Map candidate markets, gather role-fit evidence, organize sourcing notes, and prepare recruiter review queues.
Collect market examples, monitor competitor pages, turn source material into briefs, and prepare first-pass drafts.
Watch recurring inputs, reconcile lists, flag exceptions, and send structured summaries to owners.
Starting point
Start with work your team can review quickly. Add more workflows once the inputs, output, and approval rules work as expected.
$50 per month
Hosted Pro ยท 1,000 tasks included each month
Real workflow proof
This anonymized recruiting workflow shows three stages. A Gobii AI teammate clarifies the job, creates a plan, and returns a source-backed shortlist for review. Each stage gives the team something concrete to inspect.
Explore the AI sales agent workflow
FAQ
Teams usually ask these questions before AI employees touch real data or hand work to other systems.
An AI employee is software that owns a defined workstream. It gathers context, uses tools, takes approved actions, and produces output for review. Gobii uses AI teammate because people keep control while AI handles repeatable execution.
Yes. Teams can deploy AI employees when work has clear inputs, approved tools, success criteria, and review points. Start with one repeatable workflow, not a job title. A virtual AI employee can run it, document the work, and hand it back.
A chatbot answers questions in a conversation. An AI employee works across a workflow. It can browse approved sources, update structured outputs, compare information, prepare drafts, and ask for review. The key difference is sustained execution.
An AI employee can research, monitor, enrich lists, prepare documents, update spreadsheets, and create handoff summaries. It works best on repeatable tasks with clear sources, rules, and review criteria.
To hire AI employees, start with a short workflow brief. Define the goal, sources, allowed tools, output, schedule, and reviewer. A Gobii AI teammate can then run the work, flag uncertainty, and improve from feedback.
Ready to try the operating model?
Start with work your team already understands. Define the inputs, approved sources, review rules, and handoff. Gobii gives the workflow a persistent AI teammate.