AI Agent Suite

Six AI agents that run your marketing stack autonomously

Most marketing teams spend 60% of analyst time on tasks that follow a pattern: pull data, spot the anomaly, write the recommendation, update the report. Our AI agent suite handles that loop. Each agent covers one function, runs on the Claude Agent SDK, and escalates to your team only when a decision needs a human.

Deploy Your Agent Suite

View Pricing

Specialized AI agents

~40hrs

Analyst time redirected monthly

24/7

Monitoring and optimization

100%

Human-in-the-loop on spend changes

The Agent Suite

Six agents, six functions, one integrated stack.

Each agent is independently deployable and integrates with the others through shared data outputs and Slack escalation channels. Deploy one or all six.

AI SEO Agent

Content optimization, SERP analysis, entity coverage, CTR improvement.

Runs autonomously

— Daily SERP monitoring for 500+ tracked keywords
— Entity coverage scoring against top-ranking pages
— Internal link recommendations across full content library
— Meta title and description optimization at scale

Escalates when

Ranking drops >15% in 7 days or new competitor entering top 3.

Stack

Claude Agent SDK, DataForSEO MCP, Ahrefs MCP, Supabase

Full details

AI PPC Agent

Daily bid optimization, keyword discovery, ad copy testing, negative mining.

Runs autonomously

— Daily bid adjustments across all active campaigns
— New keyword discovery from search terms report
— Negative keyword mining from irrelevant queries
— Ad copy variant rotation based on CTR signals

Escalates when

Spend changes >20%, new campaign launches, CPA exceeds target by 40%.

Stack

Claude Agent SDK, Google Ads API MCP, BigQuery MCP

Full details

AI Content Agent

Brief to publish: SERP research, citation-grounded drafting, quality validation, and CMS staging.

Runs autonomously

— Keyword-grounded brief generation from SERP analysis
— Draft production using seo-kb RAG for citation accuracy
— Eight-dimension content quality validation
— Image brief generation and CMS staging

Escalates when

Validation score below 75, factual claims needing expert review, new topics outside existing KB.

Stack

Claude Agent SDK, seo_query_kb MCP, Ahrefs MCP, CMS API

Full details

AI RevOps Agent

Pipeline hygiene, deal-stage monitoring, lead scoring from signal graphs.

Runs autonomously

— Stalled deal detection and AE Slack alerts at 72-hour mark
— Contact enrichment from firmographic data sources
— Lead scoring model updates from engagement signals
— Pipeline coverage reports delivered weekly

Escalates when

Deals stalled >14 days, contacts missing required fields above 30%, scoring model drift.

Stack

Claude Agent SDK, HubSpot MCP, Salesforce MCP, Slack MCP

Full details

AI Analytics Agent

Natural-language queries on GA4 and BigQuery. Ask questions, get answers and charts.

Runs autonomously

— NL-to-SQL translation against GA4 BigQuery export
— Automated anomaly detection on core KPIs
— Weekly traffic summary generation with YoY comparison
— Chart and data table generation from query results

Escalates when

Traffic drops >20% week-over-week, conversion rate anomalies, data freshness gaps.

Stack

Claude Agent SDK, BigQuery MCP, GA4 MCP, Slack MCP

Full details

AI Reporting Agent

Weekly client reports: GSC, GA4, Ahrefs, Ads correlated to work shipped.

Runs autonomously

— Data pull from GSC, GA4, Ahrefs, Google Ads every Monday 6am
— Narrative generation correlating results to shipped work
— PDF report generation and Slack summary delivery
— YoY and MoM comparison with trend callouts

Escalates when

Data source auth failures, metrics outside acceptable variance, missed delivery windows.

Stack

Claude Agent SDK, GSC MCP, Ahrefs MCP, Supabase MCP, Slack MCP

Full details

How Autonomy Works

What runs without you. what waits for you.

Autonomous does not mean unsupervised. Every agent has a defined decision boundary. Below the line, it runs. Above the line, it alerts and waits.

Decision type	Agent handles autonomously	Escalates to human
Budget & spend	Bid adjustments within daily budget limits	Spend changes >20%, new campaign launches
Content publishing	Drafts, validation, CMS staging	Publish approval, factual claims outside KB
CRM updates	Contact enrichment, lead scoring, pipeline alerts	Deal reassignment, account owner changes
Ranking changes	Monitoring, entity gap analysis, recommendations	Ranking drops >15% on priority keywords
Data anomalies	Detection, pattern analysis, Slack notification	Root cause decisions requiring business context
Client reporting	Data pull, narrative, PDF generation, delivery	Sensitive metrics requiring strategic framing

Infrastructure

The Anthropic stack underneath every agent.

We use the same infrastructure we advise clients on. Every agent runs in daily production across 15 client engagements before we deploy it for you.

Orchestration

Claude Agent SDK

Multi-turn agent loops with tool use, retry logic, and fallback patterns. Prompt caching enabled on all static context to reduce latency by 60-80%.

Skills library

67 custom Skills

Per-client Skills files encoding brand voice, editorial standards, and domain knowledge. Loaded contextually, not globally, to stay within token limits.

Data connections

MCP servers

Pre-built MCP integrations for Google Ads, GSC, GA4, BigQuery, Ahrefs, HubSpot, Salesforce, Supabase, and Slack. Custom connectors available.

Knowledge base

seo_query_kb

Fine-tuned Qwen3.5-27B running locally via our seo_query_kb MCP tool. 100% citation rate from Ahrefs, Moz, Backlinko, and Google Search Central sources.

Validation

Anti-AI scoring engine

Eight-dimension content quality check across authenticity, specificity, data grounding, brand voice, readability, and structural integrity. Pass threshold: 85.

Notifications

Slack MCP + Hooks

Every escalation fires a structured Slack message: what the agent wants to do, the data behind the decision, the recommended action, and a cancel window before anything executes.

What the Full Suite Delivers

One SaaS team replaced three analyst roles with the full agent suite.

The Challenge

A 30-person B2B SaaS company was spending $18,000 per month on a three-person analytics and ops team whose primary output was weekly reports, bid adjustments, and content briefs. All pattern-following work. None of it strategic. The team was stretched across Google Ads management, GSC pulls, HubSpot hygiene, and monthly reporting. Nothing was getting done fast enough.

Our Solution

We deployed the full six-agent suite over eight weeks. Content optimization and SERP monitoring fell to the AI SEO Agent. Daily Google Ads bid adjustments and keyword pruning went to the AI PPC Agent. Two validated articles per week came out of the AI Content Agent without adding headcount. HubSpot stalled-deal monitoring, contact enrichment, and lead scoring updates ran through the AI RevOps Agent automatically. For analytics, the team started asking plain-English questions against their GA4 BigQuery export rather than filing data requests. Every Monday at 7am, the AI Reporting Agent delivered the weekly client summary.

Results Achieved

~160hrs/mo

Analyst hours redirected

From pattern tasks to strategic work

-31%

PPC cost per lead

After 90 days of bid optimization

Content output

Same team, without hiring

72hrs to 2hrs

Report turnaround

Weekly client report cycle

FAQ

AI marketing agent frequently asked questions

Each agent handles its defined function autonomously within set boundaries. The PPC agent adjusts bids and mines negatives daily without approval, but requires sign-off on spend changes above 20%. The content agent drafts, fact-checks, and validates before flagging for editorial review. The reporting agent compiles, correlates, and ships. The line between autonomous and escalated is defined in the engagement scope before go-live.

All agents are built on the Claude Agent SDK with prompt caching enabled to reduce latency and cost on repetitive context. MCP servers connect each agent to its data sources: Google Ads API, GSC, GA4 BigQuery export, HubSpot or Salesforce, Ahrefs, and Supabase for session data. Slack is used for escalation alerts. Google Sheets for output that non-technical stakeholders need to read. Custom Skills libraries enforce brand voice and editorial standards per client.

A single agent typically goes live in three to four weeks: one week for data source connection and testing, one week for behavior configuration and approval gate setup, and one to two weeks of supervised runs before handover. The full six-agent suite runs eight to twelve weeks for a clean deployment. We do not rush configuration. A misconfigured agent that makes autonomous decisions is worse than no agent at all.

Yes. MCP servers are the integration layer. Pre-built connections cover Google Ads, GSC, GA4, HubSpot, Salesforce, Ahrefs, and four more. Custom integrations are scoped per engagement. If your CRM or analytics tool exposes an API, we build the MCP connector. The agents themselves are tool-agnostic; the model underneath is Claude.

Approval gates are defined during the scoping call and vary by agent and client risk tolerance. Common gates: PPC bid changes above 20% require Slack approval within 4 hours or are held. Content goes through editorial QA before publish. RevOps contact updates above a volume threshold trigger a weekly review. Spend-impacting decisions never execute without at minimum a Slack notification with a cancel window.

Every agent runs with retry logic and fallback patterns. If an API call fails three times, the agent logs the failure and notifies via Slack rather than proceeding with incomplete data. Content outputs go through an eight-dimension validation script before delivery. PPC changes are staged before execution. Rollback is built into any action that writes to a production system.

Ready to Deploy?

Start with one agent or the full suite.

Book a 30-minute scoping call. We will map your highest-friction workflows to the right agents and give you a deployment plan with timelines and approval gate definitions.

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