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Service and operations

An operator that works while the team sleeps, and can show its work in the morning.

Keep scheduled reporting, checks and coordination running beyond office hours. The agent works within assigned systems and records its actions. Our own operations agent sends spending decisions and client messages to a person for approval.

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Who it is for

Teams that need this workflow.

Founders whose evenings are the operations department

Operations teams with a dozen recurring jobs that live in one person's head

Companies that want an agent on a server that is up when every laptop is closed

What it does

Always-on operations agents, by the job.

Run

Runs the daily jobs

Reports pulled, digests written, records reconciled, files moved, reminders sent: the scheduled work a person does at seven in the morning or does not do at all.

Answer

Answers the team where they work

Questions in Slack about what happened, what is due and where something lives, answered from the systems it has read access to, with the source.

Watch

Monitors its responsibilities

Pipelines that did not run, feeds that went stale, a number that moved too far: raised to a person before it reaches a client.

Record

Records everything it does

One standard: the agent knows its own activity without a gap. Every action and every message is logged, and a person can reconstruct any day from the log.

How it is built

The build, in order.

The pilot covers one defined workflow. We agree its success metric and kill threshold in writing before the build; the steps below show how this system is developed and evaluated.

List the recurring work

Every job that happens daily or weekly, who does it, what it reads, what it writes, and what goes wrong when it is skipped. The agent takes the ones with a clear input and a checkable output.

Grant access narrowly

Read access broadly, write access per system and per action, with credentials in a managed store that the agent cannot print. Spending and client messages run inside limits you write.

Run on a server

A VPS, your cloud account or a container in your data centre, so the agent is up when laptops are shut. Every file it changes carries a backup and a one-line revert.

Review the log weekly

Review failed runs, repeated alerts and actions held for approval. Use the record to fix the workflow or its rules while retaining the agreed authority limits.

In production at Strataigize

We run this ourselves.

Chuck, our AI Operations Agent, is the always-on agent that runs Strataigize's operations from a server that is up when every laptop is closed. He runs scheduled jobs, talks to the team in Slack and writes the daily digests. He also taught us the hard rules on this page: a guard that wrongly refuses is worse than the bug, an alert that fires every day is a broken alert, and a rule that lives somewhere other than the code path that executes it will eventually be skipped. Chuck himself works under our own stricter rule: anything that spends money or messages a client goes to a person first.

Chuck, our AI Operations Agent

Governance

Controls and human review.

Read access broadly, write access narrowly, granted per system and revocable
Spending and client messages run only inside limits you write; anything outside them, and any credential change, goes to a person
Every file it changes carries a backup and a one-line revert, and its log is complete by standard

The rest of the posture is published on trust and security: client-granted access you can revoke, credentials in managed stores, an AI governance summary aligned to the NIST AI Risk Management Framework, our subprocessors, and a DPA on request. We do not hold SOC 2 and we say so there.

Case studies

The work behind it, documented.

Strataigize Marketing

AI Agents for Business: Our Agency's AI Operations Agent

3 to 25 min New client onboarded, signed contract to live project24/7 Unsupervised coverage, nights and weekends included

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Strataigize Marketing

How Our Marketing Agency Uses AI Agents to Automate Busywork

40+ Estimated client tasks queued monthly7 days A week of industry news, read in minutes daily

Read the case study →

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Questions

Always-on operations agents, answered.

What is an AI operations agent?

An agent that runs continuously on a server, does the recurring work of a business on a schedule, answers the team from the systems it can read, watches the things it is responsible for, and writes down everything it did. It is the difference between an automation and a colleague who happens to be software.

What does it run on?

A server that is up when your laptops are not: a VPS, your cloud account or a container in your data centre, never someone's desktop. It connects to Slack, calendar, mail, the CRM and the tools it needs through APIs, with credentials held in a managed store it cannot print.

How is this different from Zapier or Make?

Automation tools run fixed steps when a trigger fires. An operations agent reads, decides within bounds, writes up what it found, and asks when it is unsure. Both have a place. The agent is for the work that needs judgement between the steps, and it is held to a far stricter logging standard.