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AI Automation That Gives Your Team Hours Back

The AI projects that pay off are boring on purpose: qualifying leads automatically, drafting responses, extracting data from documents, routing tasks. We build these with human oversight built in — AI does the volume, your team keeps the judgment.

This very website runs on that principle: AI generates each visitor's project roadmap, and a human consultant reviews it before anything is final.

What's included

✓ Workflow mapping — where AI actually helps
✓ Integration with your existing tools
✓ Human-review checkpoints where they matter
✓ Cost controls and usage monitoring
✓ Training for your team

See your personalized plan in 3 minutes

Free AI project analysis with readiness score, features and timeline — reviewed by a real consultant. No payment, no obligation.

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Frequently asked questions

Will this replace my staff?

The honest goal is leverage, not replacement: the same team handling more volume with less repetitive work.

What does an automation project cost?

Focused single-workflow automations start around $600–$1,500; multi-system automation platforms from $4,000.

How does the free project analysis work?

You answer a few focused questions (about 3 minutes). Our AI generates a personalized roadmap with features, phases and a readiness score — then a human consultant reviews it with you on a free call before any scope or price is final.

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What the build process looks like, step by step

Every engagement starts with a workflow audit: we document the task you want to automate in enough detail to expose the edge cases that sink most AI projects — the exceptions, the approval steps, the data formats that vary by client. From there we build a scoped proposal that names the specific tools (n8n, Make, OpenAI, Google Gemini, or others depending on your stack), the integration points, and what human review looks like at each stage. Once you approve scope, we build a working prototype first — not a demo, but something connected to your real data — so you can stress-test it before it touches live operations. Feedback rounds are structured: we fix what breaks, document what we changed, and only then move to production. You receive written documentation of every workflow so your team can maintain or modify it without us. Timelines depend on complexity; simple single-step automations typically take one to two weeks, multi-system workflows longer.

Honest guidance on cost, timeline, and what AI cannot do for you

Most AI automation projects we scope fall into one of three effort tiers. Simple automations — a single trigger, one action, one output (like routing a form submission to the right inbox) — typically take days to configure and cost less than a few hundred dollars in tooling per month. Mid-complexity workflows involving conditional logic, multiple data sources, or document parsing take weeks to build and test properly. Full custom integrations connecting proprietary systems require longer timelines and ongoing maintenance budgets. What AI genuinely cannot do: make judgment calls your team hasn't defined, handle edge cases it hasn't seen, or replace a process that isn't documented yet. If your current workflow lives entirely in people's heads, the first step is process documentation — not automation. Timeline reality: rushed AI builds create technical debt fast. A workflow that saves ten hours a week is only worth building if it runs reliably for months, not just the first Tuesday.