Pipelines, not pilots
AI automations built to run, not to demo.
We design, build, and run content and operations pipelines — logged and diffable, with a human approving every word that goes out and a named engineer on call. Research, draft, check, publish: on a schedule, under supervision.
- Human-in-the-loop by design
- Logged & diffable
- Fixed-scope pilots from $15,000
Pipeline anatomy
Idea in. Published out.
Every pipeline we ship follows the same four-stage skeleton. The specifics change per client; the skeleton doesn't.
Pipelines do the repetitive half. Your team keeps the creative half.
Idea & intake
Sources land in one place: your inbox, a form, a Slack channel, a spreadsheet. The pipeline normalizes them into work items with metadata — topic, audience, format, deadline. Nothing lives in someone's head anymore.
Agent production
Specialized agents draft the work: research agents pull facts with citations, drafting agents write in your voice (trained on your best existing content), and formatting agents adapt one draft into every channel — blog, newsletter, social, script. Each agent's output is logged and diffable.
Review gates
Nothing publishes itself. Automated checks run first — plagiarism, factual consistency, brand voice, link health. Then your team approves from a single review queue, designed for under 15 minutes a day.
Publish & measure
Approved work ships to your CMS, scheduler, or channels on your calendar. Performance data flows back into the pipeline — topics that work get prioritized, formats that flop get cut. The loop gets smarter every week.
Watch it run
A content pipeline, one morning's work.
An illustrative run log from a pipeline like the ones we build — research in, three published assets out, one rejection sent back for a second pass. Real runs are logged per client, diffable, and yours to inspect.
Where it fits
Four pipelines clients ask for most.
Content operations
Turn one idea into a blog post, newsletter, five social posts, and a video script — weekly, on schedule, in your voice. Editors approve instead of drafting from scratch.
Support triage
Incoming tickets get classified, enriched with account history, and answered with drafted replies in your tone. Agents approve or edit before send. First-response time drops from hours to minutes.
Reporting toil
Weekly status decks, KPI summaries, client reports — assembled from your tools overnight, with commentary drafted from the numbers. You review, correct, send.
Sales operations
Prospect research, personalized outreach drafts, meeting briefs, and CRM hygiene. Your reps spend their hours on calls, not on copy-paste.
Quality control
Humans decide. Machines do the typing.
The failure mode of AI automation is obvious: plausible-sounding output that nobody checked. We build the checking into the pipeline itself.
What we don't build
- Chatbots that answer off the training data with full confidence
- Auto-published content nobody has read
- One prompt, one output, fingers crossed
- Black boxes — no logs, no diffs, no "why did it say that"
What we do build
- Multi-stage pipelines with separate research, draft, and QA agents
- Automated checks (facts, links, voice, plagiarism) before human review
- A single approval queue your team clears in minutes per day
- Full run logs — every output traceable to its sources
Tooling
Boring tools, used precisely.
We don't marry frameworks. We pick the tool that fits your stack, your data, and your team's ability to maintain it — then document it so you're never locked to us.
- OpenAI API
- Anthropic Claude
- Gemini
- LangChain
- n8n
- Temporal
- Pinecone / pgvector
- Your CMS & APIs
- Slack / Teams
Deliverables
What you walk away with.
A pilot ends with a working pipeline in your infrastructure, not a demo on our laptop.
- Working pipeline — deployed in your cloud or ours, running on your schedule.
- Runbooks — every agent, prompt, and gate documented so your team can operate it.
- Review tooling — the approval queue, tuned to your team's daily workflow.
- Quality baseline — measured before/after on your actual work, not vanity metrics.
- Handover training — two live sessions with the engineers who built it.
fixed-scope pilot, kickoff to handover — no open-ended retainers
daily review budget the pipeline is designed for — not a second job
of runs logged and diffable — every output traceable
unreviewed publishes, ever — a human approves every word
What we build to — written into the pilot before we start, not claimed after.
FAQ
Asked before we start.
No. It replaces the repetitive half of their work. Every pipeline we ship keeps a human approval gate — your team reviews more output in less time, and the judgment calls stay theirs. The freed hours are yours to redeploy — teams typically point them at higher-value work, not headcount cuts.
Four layers: research agents attach citations to every claim, separate QA agents check facts against sources, automated checks verify links and voice consistency, and your team approves from a single queue. Nothing reaches your audience without a human seeing it.
Pilots are fixed-scope and fixed-price — one pipeline, 4–6 weeks from kickoff to working deployment. You approve the scope before we start, and the price doesn't move unless you add scope. We size pilots so the first win can cover the pilot's cost.
Yes — that's the default. We integrate with your CMS, CRM, helpdesk, and chat tools through their APIs. We only suggest new tools when yours genuinely can't do the job, and we tell you exactly why.
You do. Code, prompts, configs, runbooks, and credentials transfer to you at handover. We can run it for you on a managed plan, but you're never locked to us — your team can operate everything we built.
Free · 7 days · yours to keep
Know what it's worth before you pay a dollar.
Our free AI audit maps your workflows, finds the automation targets, and estimates the savings — in numbers you can check. Takes one week, costs nothing. Every build ships to our Production Standard: evals, logged runs, human approval, and a named engineer on call.