Our own content pipeline
Briefs in, drafts out, editors as the gate, with the status of every piece visible without a chase.
Built, monitored, in daily use
AI Automation
The marketing work that repeats every week, built to run itself.
An AI automation agency for marketing and content operations. WKND designs, builds and monitors the automations and agents behind your reporting, lead routing, email and SMS flows, content production and creative pipelines. Human checkpoints where it matters. Documented, monitored, and owned by you. For marketing teams at $1M to $50M companies with real repeatable volume.
Three builds first
the highest-scoring workflows from the audit, running before anything else is touched
Every build
monitored, with alerts, a documented fallback and a named owner on both sides
Yours
credentials, code, workflow definitions and documentation live in your accounts
Trusted by brands that live and die by creative performance.
Not a tool. Not an IT integrator who has never run a campaign. Not a marketing team that says it uses AI. An AI automation agency takes the work your team repeats, decides which steps a machine should do and which a person must approve, builds the system, connects it to the stack you already have, and keeps it running. WKND's scope is marketing and content operations, because that is where the repeatable work in a growing brand lives.
you build it, you maintain it, it breaks on a Tuesday
reliable plumbing, no idea what a lead is worth
marketing workflows, human checkpoints, monitored, yours
Automation is one line of our AI marketing agency work.
platform data pulled, reconciled and delivered on a schedule; the Monday report that used to take a day.
enrichment, scoring, assignment and follow-up triggers, with a person deciding anything that touches a deal.
segment logic, send triggers and content variants built and tested, approval before send.
brief to draft to edit to publish, with editors as the gate; the system behind our AI content creation work.
brief to variants to trafficking, feeding the testing machine described on our AI performance creative page.
classification and routing of inbound requests, with escalation rules a human wrote.
Positioning. The offer. Brand voice. The decision to scale or kill a campaign. Anything where the cost of a wrong answer reaching a customer is higher than the hours saved. We put a human checkpoint there instead, and we will tell you when a workflow you asked about belongs on this list.
Two kinds of build. A deterministic automation does the same thing every time and should, for anything you can write as a rule. An agent handles bounded judgment: drafting, classifying, summarizing, choosing among options, and it is reviewable by design. The failure mode in this market is an agent with no checkpoint. Ours sit wherever an output reaches a customer, a budget or a public channel.
Deterministic automation
Checkpoint at the edge: a person approves before anything reaches a customer, a budget or a public channel.
Agent
Checkpoint on the output: every draft, classification or choice is visible and approvable before it moves on.
The workflow audit scores every candidate on four tests. Repeatable: does it happen weekly or more. Information-heavy: is the work mostly moving, reading and reshaping data. Rule-describable: can your best person write down how they do it. Measurable: will we know the hours or cycle time it saved. The three highest scores are the first three builds. Everything else waits until those are running.
does it happen weekly or more
is the work mostly moving, reading and reshaping data
can your best person write down how they do it
will we know the hours or cycle time it saved
01
every repeatable process scored on the four tests
02
step by step, with the exceptions
03
deterministic steps, agent steps, checkpoints marked
04
your stack, through its APIs, with retries and fallbacks
05
a month of real data before go-live
06
alerts, documentation, ownership in your accounts
on every build, so a failure reaches an owner rather than a stakeholder.
documented for the step most likely to fail, with the manual path written down.
a new hire can follow, in language a marketer reads without a translator.
credentials, code and workflow definitions live in your accounts.
Most automations that fail were never built to survive the ordinary: an API that times out, a webhook that fires twice, a platform that throttles at month end. Ours retry with backoff, treat every step as safe to run twice, respect each platform's limits, and log what happened in language a marketer can read. A workflow that runs on a good day is a demo. One that runs on a bad Tuesday is a system.
If your best person can write the steps as rules, it is a deterministic automation and should stay one: cheaper, faster, and it never surprises you. If the step needs bounded judgment, drafting, classifying, summarizing, picking among options, it is an agent, and it gets a reviewable output and a checkpoint. We promote an automation to an agent only when the rules stop fitting reality, and we demote an agent back when the judgment turns out to be a rule after all.
Every build ships with a before and after. Hours the team spent on the workflow each week. Cycle time from trigger to done: brief to publish, lead to first touch, month end to report delivered. Error and rework rate. Cost per unit of output. Where the workflow touches acquisition, we tie it to CAC and MER. We report those numbers, not the count of tools connected.
Tools automate steps. Results come from automating a workflow end to end, with the data hygiene, the exceptions and the handoffs included. A team that buys a platform and wires three steps has moved the bottleneck, not removed it. We start from the outcome the workflow exists to produce, map every step back from it, and build the whole path, including the boring parts where the previous attempt gave up.
A workflow that handles fifty leads a week needs different guardrails at five hundred. We version every workflow definition, so a change can be rolled back; add checkpoints where new volume creates new risk; and review the checkpoint list quarterly, removing the ones the data says are no longer needed. Governance is what lets an automation scale without the team losing trust in it.
The Monday report arrives before anyone is at a desk. Leads reach a person within minutes, with the context attached. Content moves from brief to published without a project manager chasing it. And when something breaks, the alert reaches the owner before the team notices anything missing.
Hours saved per week
The time the team used to spend running the workflow by hand, counted before and after.
Cycle time
Trigger to done: brief to publish, lead to first touch, month end to report delivered.
Error and rework rate
How often the output has to be fixed, because a faster wrong answer is not a win.
Cost per unit of output
What one report, one routed lead or one published piece costs to produce now.
Three models exist in this market: a fixed fee per workflow, a package of builds with monthly monitoring, or a retainer for continuous automation. You should know which one you are buying and what it costs before the first call ends.
One workflow scoped, built, tested and handed over, priced as a single build.
A set of builds delivered together, with monthly monitoring, alerts and fixes included.
An ongoing build queue, for teams whose repeatable work keeps growing with the business.
Two builds show the pattern: one of our own pipelines and one run inside a client's stack, each with a before and after the team can check.
Briefs in, drafts out, editors as the gate, with the status of every piece visible without a chase.
Built, monitored, in daily use
Platform data reconciled on a schedule and leads routed within minutes, with a named owner on both sides.
Measured before and after
Numbers are real results; ask us for the readout.
An automation lead who runs the audit and owns the architecture, builders who have run marketing operations and know what a lead is worth, and a monitoring owner who is named on every build. A marketer is in the room for every design decision.
Runs the workflow audit and owns the architecture, from the first map to the handover.
People who have run marketing operations and know what a lead is worth before they automate it.
Named on every build, alerted before your team notices a missing report or a stalled lead.
The working relationship
One person at WKND and one on your team own each build, so a broken step has somewhere to go.
Anywhere an output reaches a customer, a budget or a public channel, a person approves before it ships.
Credentials, code, workflow definitions and documentation sit in your accounts from the first build.
The internet is filling up with AI slop. We don't ship it.
Every asset is human-directed, briefed by strategists, refined by creatives, approved before it runs.
On-brand, always, your voice and guidelines are the guardrails the AI works inside.
Accountable to performance, if it doesn't earn its spend, it doesn't stay live.
An AI automation agency designs, builds and monitors the automations and agents that run repeatable work. WKND's scope is marketing and content operations: reporting pipelines, lead routing and CRM flows, email and SMS flows, content operations from brief to publish, creative-production pipelines and support triage. You get working systems with human checkpoints, documented and owned by you, not a tool subscription and a tutorial.
They find the work that is repeatable, information-heavy and rule-describable, build the automation or agent that does it, put a human checkpoint wherever an output reaches a customer or a budget, connect it to your existing stack, and monitor it so it keeps running when an API changes. The good ones also tell you what not to automate.
Three common models: a fixed-fee build per workflow, a package of builds plus monthly monitoring, or a retainer for continuous automation work. Whatever the model, you should be able to see the price before the first call ends and the hours saved after the first month.
It is worth it when you have real repeatable volume: multi-channel content, multi-market reporting, high lead flow, or a creative-testing cadence that eats a team's week. It is not worth it for one-off tasks, or for a process nobody has defined yet, because automating a mess produces a faster mess. WKND's workflow audit tells you which side you are on before you spend.
An AI marketing agency is accountable for marketing outcomes: creative, media, search, content. An AI automation agency is accountable for systems: the workflows and agents that make those outcomes cheaper and faster to produce. WKND does both, and the automation work most often starts inside the marketing engagement, where the repeatable work is.
We map the current workflow step by step, decide which steps are deterministic and which need bounded judgment, build deterministic automations for the former and reviewable agents for the latter, connect them to the systems you already use through their APIs, add retries and fallbacks, and set the human checkpoint before anything reaches a customer or a budget. Nothing is ripped out to make room for a tool.
You do. Credentials, code, workflow definitions and documentation are handed over in your accounts, so the system keeps running if you stop working with us.
Every build ships with monitoring and alerts, a documented fallback for the step that failed, and a named owner on both sides. Most breaks are an API change or a credential expiry; the monitoring catches them before your team notices a missing report or a stalled lead.
The workflow audit scores your repeatable marketing work and hands you the first three builds, priced.