A new hire that
never sleeps.
An AI Employee handles a full role where the work is computer-based. Not a chatbot, not a copilot. A coworker built for one job, wired into the same tools the rest of the team already uses.
What it isn't.
What it is.
Most AI pitches are chatbots in a trench coat. AI Employees are not that. Here is the precise difference, side by side, so we do not waste your time on a misunderstanding.
Five behaviors that matter.
Five behaviors that separate an AI Employee from a generic AI tool plugged into a workflow. Every Sync-built AI Employee has all five.
- 01
Trained on the partner business.
Documents, recordings, prior work, the systems the team already uses. The AI Employee learns the role from real artifacts, not a generic prompt or a stock LLM.
- 02
Operates inside the team.
It can have its own seat in the org chart, a Slack handle, an email address, a Portal account. Other staff hand it work the way they would hand a coworker.
- 03
Delivers structured output.
Drafts, decisions, completed tickets, finished documents. Output goes to a human checkpoint where useful and direct to the system of record where appropriate.
- 04
Flags what it cannot decide.
Edge cases, missing information, judgment calls outside its training. It pauses, surfaces the question, and waits for a human answer before continuing.
- 05
Improves with the work.
Every accepted output, every correction, every edge case becomes training data. The role gets sharper month over month, without re-engineering.
Patterns we've shipped before.
Patterns that show up across our partner book. Each one is built to the specific business, never pulled from a catalog. Numbers below are real ranges from partner builds.
Proposal Desk.
Ingests intake forms, drafts scoped proposals from the partner playbook, formats to the partner template, routes to a partner for review and signature.
Service Call Attendant.
Picks up inbound calls, identifies the issue, resolves recurring problems on the line, and books a tech with full context when a human visit is needed.
Invoice Reconciler.
Compares invoices to POs and contracts, flags discrepancies, and produces an exception report for the controller.
Lead Qualifier.
Reviews inbound leads against ICP criteria, enriches from public data, drafts a first reply, and routes hot leads to the right rep.
Web Developer.
Senior-level. Picks tickets off the backlog, writes the code against the partner's stack, opens a PR with tests and a changelog, and commits and pushes.
Social Media Marketer.
Drafts on-brand posts across LinkedIn, Instagram, and X, sources or generates visuals, schedules the calendar, and surfaces what is performing every Monday morning.
Ad Manager.
Runs paid campaigns across Google and Meta. Monitors CPA daily, reallocates budget across creative and audiences, and drafts new variations when fatigue hits.
Title Processor.
Handles ~80% of the role: title commitments, chain of title, deeds, POAs, payoff and lien research across county records, and settlement statements. A team member reviews finals for 15 minutes per transaction.
Financial Analyst.
Pulls portfolio data, generates client review packs, summarizes market activity, and drafts quarterly commentary for the advisor's signature. The advisor reviews and delivers.
Competitor Analyst.
Tracks competitor pricing, product changes, hiring signals, and content cadence across a watchlist. Delivers a weekly brief with what changed and why it might matter.
Executive Secretary.
Owns the executive's day end to end. Books and reschedules meetings, manages travel and expense filings, coordinates vendors and gifts, prepares daily prep packets, and runs the calendar without the executive in the loop.
Civil Engineer.
Drafts CAD updates, runs preliminary calcs against the design intent, and prepares submittal packages and RFI responses for the licensed engineer to review and stamp.
Kickoff to first hire.
The build path for a new AI Employee. Most go live in 4 to 8 weeks from the strategy session, depending on the complexity of the role.
Map the role.
Sit with the person doing the work today. Document the inputs, the outputs, the edge cases, the systems.
Train on real work.
We build the role on top of your data, recordings, and prior outputs. Iterate against examples until it ships finished work.
Deploy with checkpoints.
Goes live with a human checkpoint on every output. We tune the trust threshold as accuracy proves out.
Operate and improve.
Every correction is training data. The role gets sharper. We expand scope as the team's confidence grows.
What's the first role you would stop doing by hand?
Tell us about it on a 30-minute discovery call. If we can build it, we will say so. If we cannot yet, we will say that too.