03 · Amplify
Put AI agents to work on the tasks that scale your team.
Arcalea designs, builds, and runs custom AI agents and automation that take on the repeatable, judgment-heavy work in your marketing and operations, so your people spend their time on the decisions that actually need a human. We build on OpenAI, Anthropic Claude, and Google Gemini, model-agnostic by design, with human-in-the-loop checkpoints wherever the work touches customers or budget.
For CMOs · CTOs · COOs · Operations and Marketing Leaders
What we build.
Off-the-shelf automation vs Arcalea agentic integration
| Off-the-shelf automation | Arcalea agentic integration |
|---|---|
|
Executes fixed rules
|
Executes goals that need judgment
|
|
Generic templates
|
Scoped to your workflows
|
|
A bolt-on tool
|
Integrated with your CRM and data
|
|
No oversight model
|
Human-in-the-loop on external actions
|
|
Single-vendor lock-in
|
Model-agnostic, updated as models improve
|
How an agentic engagement runs.
What every engagement includes.
What you get
Working agents and automations in production, integrated and documented; ongoing maintenance and monitoring; and SLA-based uptime guarantees on production systems.
Standards and safeguards
Human-in-the-loop on any agent that touches external communications or financial decisions; model-agnostic architecture so systems are not locked to one vendor; secure handling of your data; and clear escalation criteria on every agent.
Engagement and investment
Each engagement is scoped from a discovery of your workflows, which produces a fixed proposal. Delivered as a defined project or an ongoing program, depending on how much you want to automate.
What people ask before choosing Arcalea for agentic integration.
Marketing automation executes predefined sequences based on rules and triggers, for example, if a contact opens an email, send a follow-up in three days. Agentic AI executes goals rather than rules. An agent can be tasked with monitoring competitor pricing, summarizing changes, drafting a response brief, and routing it to the right person, without a human specifying each step. Arcalea builds both and typically deploys them as a layered system: automation handles repeatable sequences, agents handle judgment-dependent tasks.
We start by identifying the highest-value repeatable judgment tasks in your marketing or operations workflow, typically competitive monitoring, performance reporting, content updates, and lead research. Each agent is scoped with clear inputs, outputs, and escalation criteria. Production agents are built on OpenAI, Anthropic Claude, or Google Gemini depending on task requirements. Human-in-the-loop checkpoints are designed into any agent that touches external communications or financial decisions.
We run production agentic systems on OpenAI, Anthropic Claude, and Google Gemini, depending on the task profile. Model selection is driven by task requirements, not vendor preference, and the architecture is model-agnostic so systems can be updated as models improve.
Every agent is scoped with explicit inputs, outputs, and escalation criteria, and any agent that touches external communications or financial decisions has a human-in-the-loop checkpoint. You stay in control of the decisions that matter while the agent handles the work around them.
No. The architecture is model-agnostic. We select the model that fits each task and can update systems as the models improve, so you are not locked to a single vendor.
A scoped automation or first agent typically moves from discovery to production in a matter of weeks, depending on the number of systems it touches. We maintain everything after deployment and provide SLA-based uptime on production systems.
Related Reading
Keep exploring how the work connects across the Arcalea system.
Data & AI Systems
Attribution, audience modeling, and the data pipelines that feed every agent.
Read article →How Arcalea Works
Intelligence before action: the model behind every engagement.
Read article →The Arcalea Platform
Galileo, Compass, AEO Index, and QMA, the engine under the work.
Read article →Ready to put agents to work on your highest-cost manual tasks?
The first step is a short discovery of your workflows to find where automation and agents will pay off fastest. We come back with a scoped plan and a fixed proposal.