Apparel · DTC
22NatiON
+26%
Conversion rate
Ongoing
Engagement
Steady
Audience growth
A precision launch that turned a new collection into a sell-out moment.
All services
Service · AI Automation
AI automation that actually ships.
Most agencies sell AI as a buzzword. We build and run the actual systems: lead enrichment, customer research, content workflows, and reports that write themselves. People stay in the loop wherever judgment matters.
Outcomes
What we engineer for.
Targets, not promises — the metrics every engagement is measured against. Real numbers from real clients live in the case studies below.
10×+
Speed on audience research
−60%
Manual reporting time
24/7
Lead enrichment cadence
Weeks
Time to production system
Who it's for
The shape that fits.
AI automation pays back fastest where there's repeatable knowledge work and clean data. The clients who get the most leverage tend to share these traits:
Ideal clients
- Founder-led businesses where senior people are stuck doing manual work
- Sales-led companies with high lead volume and inconsistent qualification
- Marketing teams drowning in reporting requests from leadership
Industries
- Professional services
- B2B SaaS
- Financial services
- Healthcare & wellness
- Local & home services
Stages
- Teams of 10–100 hitting operational ceilings
- Companies in PE/VC scaling phases
- Established operators automating before scaling headcount
Methodology
How we run AI Automation.
Every AI automation engagement runs through the same four stages. We don't ship demos. We ship working systems with documentation, monitoring, and a runbook.
- 01
Workflow audit
We sit with the people doing the work, document the steps, identify what's repeatable, and map where AI adds leverage versus where it adds risk. Not everything should be automated.
- 02
System design
Each workflow is designed step by step: inputs, transformations, validation, human-review gates, output. We pick tools (Clay, n8n, Zapier, Make, custom code, the OpenAI / Anthropic APIs) based on the job, not the trend.
- 03
Production build
Systems are built with monitoring, error handling, and clear ownership. People review where judgment matters: copy approval, lead qualification, anomaly response. Quality holds at scale because someone owns it.
- 04
Operating handoff
We document the runbook, train your team, and stay on retainer for the first quarter to tune. The system is yours when we're done, not a black box that breaks the moment we leave.
What's included
The deliverables.
What gets built inside a typical AI automation engagement.
Lead enrichment & scoring
Inbound and outbound leads enriched with firmographic, intent, and persona data, then scored against your ideal customer profile using a model trained on your closed-won history.
Content & creative pipelines
Brand-voice generation pipelines for ad copy, email, social, and short-form video scripts. A creative lead reviews every output before it ships.
Reporting agents
Weekly performance digests compiled automatically from Meta, Google, GA4, and your CRM, written in your team's voice instead of template English.
Customer research
Customer-call transcripts, support tickets, and review data clustered into audiences that inform creative, copy, and product positioning.
Operations runbook
Documentation of every workflow, owner, monitoring alert, and escalation path, so your team can run the system without us.
Where AI changes the math
Operational, not theoretical.
Most agencies say they 'use AI.' Here's what that actually looks like in production for our clients.
01
Structured prompting, not chat
Production systems use structured prompts with explicit schemas, validation, and retry logic, not a teammate copying outputs out of ChatGPT. The difference is reliability and an audit trail.
02
Human-in-the-loop where it matters
Every system has a defined gate where a person reviews. Copy ships through editors. Leads route through a qualifier. Reports are signed off before they leave the building. Speed without judgment is just faster mistakes.
03
Tool-agnostic by design
We build on Clay, n8n, Make, Zapier, custom code, and the major model APIs depending on the workload. Nothing is locked into a single vendor, so when models or pricing change, the work doesn't break.
Selected work
AI Automation in production.
2024
Frequently asked
Quick answers.
- Is this AI strategy or AI implementation?
- Both, but heavily weighted toward implementation. We won't ship a strategy deck without owning the systems that come from it. The deliverable is working software, documented and monitored. Not a roadmap.
- Which tools do you build on?
- Tool selection is workload-driven. Lead enrichment usually runs on Clay. Workflow orchestration on n8n, Zapier, or Make. Generation pipelines on the OpenAI and Anthropic APIs depending on the use case. We avoid lock-in.
- Do you replace our marketing team?
- No. We make it harder to replace them. The goal is leverage, not headcount reduction. Your best people get freed from manual work to do the parts that need judgment.
- How long does a build take?
- A first production system typically ships in 4–8 weeks, depending on data readiness and the workflow's complexity. We size projects against business value, not engineering time.
- Who owns the systems we build?
- You do. We document everything, train your team, and the runbook lives in your tools. We stay on retainer if you want ongoing optimization, but the system isn't ours to take with us.
Related services
Often runs alongside.
01
Lead Generation
Qualified, sales-ready inbound. Paid acquisition, landing pages, scoring, and CRM handoff designed as one machine.
02
CRM Systems
CRM implementation, automation, segmentation, and email programs that turn one-time buyers into repeat revenue.
03
Content Production
Short-form, long-form, talent, and post, run on an editorial calendar and built to drive both brand and pipeline.
Engage
Ready to put AI Automation to work?
Most engagements start with a 30-minute call. We'll walk through your goals, your numbers, and what the first 90 days should look like.