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Engagement blueprints

Our methods, on display.

We're a senior engineering team — the people who'd run your engagement have shipped AI pipelines, rescued failing deployments, and operated production infrastructure for years. This page shows the exact playbook we'd run for you — phase by phase, with the success criteria we'd be measured against — and one production system we run for ourselves, every weekday.

What every engagement gets

Fixedprice on fixed-scope pilots — it doesn't move unless you change the scope
Yourscode, docs, and IP in your repos from day one — operable without us
Namedengineer on call, runbook in hand — AI with an on-call rotation

The full set of commitments lives on our Production Standard page.

Engagements

The playbook, phase by phase.

Engagement blueprints drawn from our team's shipped work — how we'd run these engagements for you. Each one shows the situation we'd walk into, the phases we'd run, and the success criteria we'd sign up to.

Engagement blueprint Engineers reviewing an automation pipeline dashboard on large monitors

AI Automation · 6-week pilot

AI content pipeline for a B2B marketing team

The situation we'd walk into: a five-person marketing team producing genuinely good content — but each asset takes weeks from brief to published, and the backlog of unwritten topics keeps growing. Publishing is logistics, not marketing.

What we'd build: a pipeline grounded in their own documents, with human approval gates on every publish decision. Week 1–2: workflow mapping and evals. Week 3–4: pipeline build against versioned prompts. Week 5: hardening and failure-mode tests. Week 6: handover — their team publishes unassisted while we watch.

≤ 48 hrssuccess criterion: asset cycle, brief to published

30 / mosuccess criterion: assets published with the same team

0success criterion: unreviewed publishes, ever

Tech: LLM orchestration grounded in the client's knowledge base, vector store for brand documents, CMS webhooks, review dashboard with human approval gates.

Model: fixed-scope 6-week pilot from $15,000, then optional monthly runbook support.

See the 6-week pilot

Engagement blueprint Server operations engineer monitoring deployment infrastructure

DevOps · 4-week rescue

DevOps rescue for a SaaS scale-up

The situation we'd walk into: a growing engineering team deploying manually on Friday nights — each deploy a two-hour window with a nervous team, and deploy-caused outages piling up. Releases are the bottleneck, not the code.

What we'd build: stabilize first, then rebuild CI/CD with per-branch preview environments. Week 1: incident review and quick wins. Week 2–3: pipeline rebuild, infrastructure-as-code. Week 4: cutover with rollback drills and full documentation.

≤ 15 minsuccess criterion: deploy time, fully automated

Dailysuccess criterion: deploy cadence with zero downtime

−70%success criterion: change-failure rate after cutover

Tech: CI/CD pipelines, infrastructure-as-code, cloud-native monitoring and alerting.

Model: fixed-price 4-week rescue, then optional monthly pipeline ownership.

Book the pipeline review

Engagement blueprint Creative operations team working together around a shared workspace

Managed infrastructure · monthly

Managed infrastructure & security for a services firm

The situation we'd walk into: a 40-person firm running client work on infrastructure nobody owns. The cloud bill drifts upward every quarter, patching happens when someone remembers, and leadership is one near-miss away from a very bad day.

What we'd do: harden everything, take ownership, and publish our response times in writing. Security posture review and backup testing first; then centralized logging, alerting, and automated patching with tested restores.

< 15 mincommitment: P1 incident response, published SLA

−20%target: cloud spend in the first quarter, or we show why not

100%commitment: backups with tested restores

Tech: cloud security posture tooling, centralized logging and alerting, automated backup and disaster-recovery testing.

Model: monthly managed plan with a fixed incident-response SLA.

See the health check

Our own system — live Team collaborating around a table with laptops

AI Automation · running now

Our own content engine

What we run for ourselves: the same pipeline we sell. Every weekday, our system drafts an article from fresh research; a human reviews, edits, and publishes. It's how this site's Insights section stays current — and it's the system we'll show you, live, on a working call.

Why it matters: most AI vendors demo. We operate. The evals, the approval gates, the runbook, the on-call rotation — everything on our Production Standard page is what this pipeline runs on. If our own system went down tomorrow morning, you'd read about the fix here.

5 / wkdrafts produced from fresh research

100%human-reviewed before anything publishes

Liverunning since September 2026 — output in Insights

Ask us: on any working call, we'll screen-share the pipeline, the evals, and the approval queue. No slides.

Read the Production Standard

Senior delivery

Senior engineers. Proven methods.

You're not buying our learning curve. The engineers who scope your engagement are the ones who build it — senior people, named on your runbook, on call when it matters. Fixed pricing, production-grade methods, and a playbook we run the same way on our own systems — because we do.

Run the free audit Read the Production Standard

Next step

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