Claude Agentic Workflows

Claude workflows that run your processes without manual intervention

A workflow built on Claude is not a chatbot with extra steps. It is a system where Claude reasons about what to do next, calls the right tools in the right sequence, handles errors without stopping, and produces structured outputs that downstream systems can use. We have mapped 120 SEO automation workflows on this stack and run them daily across 15 clients via n8n and Claude Code. That operating experience is what we bring to your workflow design.

Build Your Workflows

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120

Mapped automation workflows in our stack

15+

Client workflows running daily

Skills orchestrated by our workflow system

MCP integrations powering live data access

Workflow Types We Build

Six agentic workflow patterns we build for production teams.

These are not theoretical architectures. They are patterns we run in our own system and build for clients.

Research Agents

Claude-powered research workflows that gather information from multiple sources, combine it coherently, and produce structured documents without human coordination of each step. A research agent takes a brief, plans a research strategy, queries the right sources (web, internal databases, MCP-connected APIs), evaluates source quality, resolves contradictions, and produces a structured research document. What takes a human analyst 3-4 hours takes the agent 15-20 minutes.

Multi-source research coordination
Source quality evaluation
Contradiction detection and resolution
Structured output for downstream use

Content Refresh Agents

Agents that identify underperforming content, diagnose why it is underperforming, generate specific improvement recommendations, and execute the rewrites. Our own content refresh workflow connects GSC data (via MCP) to identify pages where rankings or CTR have dropped, runs a content audit against current SERP leaders, generates a prioritized improvement plan, and queues rewrites with the relevant brand-specific Skill. The whole sequence runs without a human initiating each step.

Performance data integration via GSC MCP
Automated SERP gap analysis
Brand-specific rewrite execution
Before/after performance tracking

SEO Monitoring Agents

Continuous monitoring agents that track keyword rankings, traffic trends, backlink changes, and technical health. When a metric crosses a defined threshold, the agent does not just send an alert. it diagnoses the likely cause, cross-references with other data sources to confirm the hypothesis, and drafts a recommended action. We run this pattern across all 15 clients. The agent surfaces the problems worth a human's attention.

Multi-signal threshold monitoring
Automated diagnosis and root cause analysis
Cross-source correlation for confirmation
Prioritized action recommendations

Report Generation Agents

Agents that pull data from your analytics stack, structure it into a coherent narrative, flag the metrics that need attention, and produce client-ready reports. Our weekly report workflow pulls GSC, GA4, and BigQuery data via MCP, runs the numbers through our analysis framework, and produces structured reports for each of our 15 clients. A process that previously took 6-8 hours per week takes under 30 minutes.

Multi-source data aggregation
Automated narrative generation
Anomaly detection and flagging
Client-ready output formatting

Alert and Escalation Workflows

Workflows that monitor your systems, detect conditions that require human attention, and route alerts to the right person with enough context to act immediately. Not every anomaly warrants a human response. An alert workflow that classifies incoming signals, determines severity, enriches the alert with diagnostic context, and routes only the high-priority items to a human reviewer reduces alert fatigue without increasing response time.

Signal classification and severity scoring
Alert enrichment with diagnostic context
Smart routing based on alert type
Escalation path definition and testing

n8n + Claude Orchestration Workflows

n8n is the workflow automation layer that schedules, triggers, and orchestrates Claude-powered processes. A workflow that runs every Monday, pulls data from three sources, feeds it to Claude for analysis, and posts the results to Slack requires n8n for the scheduling and orchestration. Claude for the reasoning and synthesis. and MCP servers for the data access. We design and build the full stack.

n8n workflow design and implementation
Claude API integration within n8n nodes
Scheduled trigger configuration
Error handling and retry logic

How We Build Workflows

Four stages from process audit to production automation.

Step 01

Workflow selection and scoping

Not every process should be an agentic workflow. We start by identifying which of your existing processes have the right characteristics: clear inputs and outputs, defined quality criteria, repetitive enough to justify build time, and high enough volume or frequency to produce real ROI. The scoping session produces a ranked list of workflow opportunities with estimated build times and projected time savings.

Step 02

Architecture design and tool selection

We design the workflow architecture: the sequence of Claude actions, the tool calls required, the data sources accessed, the error handling paths, and the output format. For n8n-orchestrated workflows, we design the node graph before touching n8n. For Claude Code-based workflows, we design the agent loop and tool set. The architecture document is reviewed before build starts.

Step 03

Build and integration testing

We build against your real data and systems. Research agents get tested on your actual research briefs. Content refresh agents get tested on your actual underperforming pages. Monitoring agents get tested on your actual metric thresholds and historical data. A workflow that only works on synthetic test data is not a production workflow.

Step 04

Production deployment and monitoring setup

We deploy the workflow, configure monitoring for the workflow itself (not just what it monitors), and run it in parallel with the existing manual process until your team is confident in the outputs. We document the workflow, including how to modify triggers, adjust thresholds, and debug common failure modes. You own the workflow; we hand it over in a state you can operate.

120 Workflows in Production

How our n8n + Claude automation stack handles 15 clients with a team of six.

The Challenge

A six-person agency managing 15 active SEO clients generates an enormous amount of repetitive high-stakes work: weekly performance reports, content audits, keyword monitoring, backlink tracking, schema validation, and client communication prep. At the individual task level, these are straightforward. At 15-client scale, running them manually is the entire job.

Our Solution

We mapped 120 recurring workflow types and built automated versions of the highest-volume 40. Our n8n instance triggers Claude-powered workflows on schedules: Monday morning briefings that pull live data from GSC, GA4, and Ahrefs via MCP and produce per-client status summaries; weekly reports that aggregate performance data and generate the narrative automatically; content monitoring alerts that diagnose ranking drops and draft action plans before the analyst opens their laptop. Claude handles the reasoning. n8n handles the scheduling. MCP handles the data access.

Results Achieved

40+

Recurring workflows automated

From a mapped 120 total

~85%

Weekly reporting time

Reduction across all 15 clients

Same-day

Client response time on alerts

vs. next-morning previously

2-3 days

New workflow deployment time

Once architecture is established

Who This Is For

Four teams ready for agentic workflows.

Operations teams with high-volume repetitive processes

The problem

Your team runs the same analysis, the same report, the same research sequence every week. Every hour spent on repetition is an hour not spent on the judgment calls only humans can make.

How we help

We identify which of your repetitive workflows have clear enough criteria to automate, build them on the Claude + n8n stack, and measure the time recaptured.

Marketing teams managing multi-channel content operations

The problem

Content refresh, brief generation, performance monitoring, and reporting across multiple channels and stakeholders requires coordination that is hard to scale manually.

How we help

We build content operations workflows that handle the mechanical coordination automatically, surfacing only the decisions that need a human strategist.

Agencies scaling from boutique to mid-market

The problem

You are adding clients faster than you can add headcount. The processes that worked at 5 clients break at 15. Automation is the only path to scaling without proportional cost.

How we help

We audit your highest-volume processes, identify the automation opportunities, and build the workflow system that lets you serve more clients with the same team.

Product teams building workflow automation into their product

The problem

You want to offer Claude-powered workflow features to your users but need a reference architecture that handles the edge cases correctly before you ship it.

How we help

We build and test the workflow architecture against real use cases, then document the patterns your engineering team can implement in your product.

FAQ

Claude agentic workflows frequently asked questions

Basic automation follows fixed rules: if X, then Y. Agentic workflows use Claude to reason about what to do next based on the current state of the task. If the research agent cannot find a good source for a claim, it decides to try a different search approach rather than failing. If the content refresh agent identifies a new competitor that was not in the original brief, it incorporates that finding. The reasoning capacity is what makes it agentic.

We build on n8n because it is what we run in production. But the patterns work on other orchestration platforms. Zapier, Make (formerly Integromat), AWS Step Functions, or custom Python orchestration can all serve the same scheduling and triggering role. If you have an existing automation stack, we design the Claude workflow layer to integrate with it.

Error handling is a first-class design concern in every workflow we build. We define explicit error states, retry logic for transient failures, escalation paths for cases that require human attention, and fallback behaviors when primary data sources are unavailable. A workflow that fails silently or stops on unexpected input is not production-ready.

A simple linear workflow (one input, one Claude call, structured output) takes 1-2 weeks. A multi-step workflow with external data sources, conditional logic, and error handling takes 3-5 weeks. A complex orchestration workflow with multiple Claude agents, MCP integrations, and downstream system writes takes 5-8 weeks. We scope precisely after reviewing your specific workflow requirements.

Yes. We document every workflow with a technical spec covering the trigger configuration, the Claude prompt used at each step, the tool calls involved, the error handling paths, and how to modify thresholds and outputs. n8n workflows are visual and modifiable without code. Claude prompts in the workflow are plaintext and editable. You own the workflow and can extend it without us.

Ready to Automate Your Workflows?

Let's map your processes and build the first workflow.

A process audit, workflow architecture design, and a production build. Your first automated workflow is running within 3-5 weeks.

Process audit and workflow opportunity ranking included
Architecture designed before build starts
Production deployment with monitoring setup