AI Workflow Automation Services: We Build It, Deploy It, Run It

AI workflow automation services are a delivered engagement — not a tool subscription — where a partner designs, builds, and operates a production AI workflow on your behalf. Our model is Discovery → Build → Run: we scope and baseline the workflow, build it against your real systems with an eval harness and reviewer queue, then run it with weekly KPI reporting. You get a governed, owned workflow, not a Zapier flow you have to maintain yourself.

Zapier, Make, n8n, and Gumloop are no-code tools: you (or a low-cost agency) chain pre-defined integrations that break when an input changes and carry no governance. AI workflow automation services are the delivery layer above that — we redesign the workflow around AI, ship it to production traffic, and add the things no-code glue lacks: audit logs on every inference call, versioned prompts, source allow-lists, NIST AI RMF mapping for regulated work, and named reviewers with SLAs. The wedge is production-grade and governed versus no-code-glue.

Phased fixed-price. Discovery: $5-8k for 2-3 weeks. Build: $15-40k for 6-10 weeks depending on integration depth and risk lens. Run: $2-6k/month, optional, month-to-month. Total year-1 typically $25-90k for a focused workflow — far below traditional consulting builds for an equivalent production system, and the right comparison to a low-trust no-code agency is governance and production-readiness, not just price.

AI business automation is the use of AI as the operating layer of a business workflow — intake, classification, retrieval, drafting, decisioning — with humans handling judgment, exceptions, and policy. It is distinct from RPA (rule-based) and from 'AI features' (a chat button bolted onto an existing process). The workflow itself is redesigned around AI.

Phased fixed-price. Discovery: $5-8k for 2-3 weeks. Build: $15-40k for 6-10 weeks depending on integration depth and risk lens. Run: $2-6k/month, optional, month-to-month. Total year-1 typically $25-90k for a focused workflow — orders of magnitude below traditional consulting builds for an equivalent production system.

Thin-slice production deployment in 6-10 weeks from Discovery start: 2.5 weeks Discovery (scope, baseline, systems, risk model), then 6-10 weeks Build (architecture, eval harness, reviewer queue, KPI dashboard, thin-slice shipped to production traffic). Optional Run phase runs continuously after that with weekly KPI reporting.

Any high-volume, structured-but-messy workflow with a measurable outcome. The best candidates: customer service (intent + grounded answers), document processing (extraction + validation), sales prospecting (signal-driven outbound), compliance triage (alert routing + evidence assembly), executive reporting (data → narrative), claims/case processing (intake → decision support). The wrong candidates: politically charged decisions with no measurable baseline, or workflows with insufficient volume to justify the build.

RPA executes rule-based scripts on structured data — it breaks when the input shape changes. Workflow tools (Zapier, n8n) chain pre-defined integrations — they don't reason. AI business automation handles unstructured input, adapts to exceptions, and makes context-aware decisions while routing low-confidence cases to humans. It is the operating layer above the integration layer, not a substitute for it.

You own everything: prompts, evaluation harness, code, configs, runbook, operating playbook. Run is month-to-month with no notice period. Most clients keep us on Run for 6-12 months while their team learns the operating model, then take it in-house. The Build SoW includes a full handover plan; the engagement is designed to survive our absence.