An AI automation agency for the GTM work your team copy-pastes every day.

Zapier setup ships a workflow. AI automation engineering ships a workflow that works reliably on real-world data with measurable error rates, observable logs, confidence routing, and a defined fallback when the AI gets it wrong. The first one is task automation. The second one is production AI engineering. Different work, different reliability.

Whichever fits the job. GPT-4o for general reasoning and tool use. Claude (Anthropic) for long-context structured outputs. Gemini for multimodal (images, video). Fine-tuned smaller models (or open-source like Llama / Mistral) where cost and latency dominate. We benchmark on your real data; we do not pick the trendy model.

Three layers. (1) Every workflow has a confidence check on its own output before delivery. (2) Low-confidence outputs route to a human reviewer with the AI's reasoning attached. (3) Critical workflows (anything involving billing, contracts, customer commitments) get human-in-the-loop confirmation on every run. We design for the workflow tolerating mistakes; if a workflow cannot tolerate any error rate, we don't build it.

Depends on volume and model. Typical revenue/ops workflow: $50 to $500/month in model API costs at moderate volume. Heavy-volume workflows (50,000+ runs/month): $1K to $5K/month. We track cost per workflow run from day 1; if the cost climbs, we surface it before it becomes a budget surprise.

Your existing tools. Workflows ship on Clay, Make.com, n8n, Cloudflare Workers, your data warehouse, your CRM. We do not build on proprietary 'Growleads platforms' you have to keep paying for. The point of AI automation is that your team can run it; that only works on tools your team uses.

Every workflow is versioned. When a model is updated, we run the previous workflow against the new model on a sample of recent runs and check accuracy. If accuracy drops, we adjust prompts/few-shot examples. If accuracy holds or improves, we promote the new model. The team doesn't see the change.

Yes. 60-day post-launch period includes operator training: weekly sessions on how to read the workflow logs, how to adjust confidence thresholds, how to debug a failed run. The goal is that day 60 onwards your team owns the work, with us on call for genuinely hard issues.

You do. All workflows, prompts, scope cards, model configurations, observability dashboards, and API keys are in your accounts from day 1. We give a 14-day handover with a recorded walkthrough of every production workflow. Nothing is locked behind a Growleads-owned account.

We do not publish a number because every engagement is sized to the number of workflows, complexity per workflow, and model API budget. What we will say upfront: 8 to 12 week fixed-scope build engagement with 60-day post-launch advisory, priced per workflow shipped to production, not hourly. The first call gives you a number tailored to your scope.

A marketing automation agency wires email flows and nurture tracks. We build AI workflow automation across the whole GTM motion: lead enrichment, account scoring, meeting briefs, deal summaries, and follow-up drafts, on Clay, Make, n8n, and the model that fits the task.

It overlaps, but we are narrower on purpose. Business process automation cleans up generic ops; we point AI workflow automation at the GTM work, lead enrichment, scoring, meeting briefs, and follow-ups, that directly feeds pipeline.