The infrastructure behind every intelligent decision.

Multi-touch attribution is a method of assigning revenue credit across multiple marketing touchpoints in a buyer's journey, rather than giving all credit to the last click or first interaction. It matters because B2B sales cycles typically involve 8 to 12 touchpoints across multiple channels before a deal closes. Without multi-touch attribution, paid media, organic search, email, and events are all competing for credit they partly deserve, which leads to misallocation of budget. Arcalea's Galileo platform builds custom multi-touch models from first-party CRM data, eliminating walled-garden bias.

Marketing automation executes predefined sequences based on rules and triggers. For example, if a contact opens an email, send a follow-up in 3 days. Agentic AI executes goals rather than rules. An AI 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.

Arcalea integrates with Salesforce, HubSpot, Microsoft Dynamics, and custom CRM systems. On the ad platform side, integrations cover Google Ads, Meta, LinkedIn, Microsoft Advertising, and programmatic DSPs. Analytics integrations include Google Analytics 4, Adobe Analytics, and custom data warehouses. Offline data such as event attendance, direct mail, and field sales activity is handled through custom ingestion pipelines. All integrations feed Galileo to maintain attribution completeness.

Arcalea starts by identifying the highest-value repeatable judgment tasks in a client's 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.

A standard CRM-to-attribution pipeline with 3 to 5 data sources typically takes 4 to 6 weeks to design, build, test, and deploy. More complex pipelines involving custom data transformations, offline data ingestion, or real-time streaming requirements take 8 to 12 weeks. Arcalea maintains all pipelines after deployment and provides SLA-based uptime guarantees for production systems.

Arcalea runs production agentic systems on OpenAI GPT-4o, Anthropic Claude, and Google Gemini, depending on the task profile. GPT-4o is used for structured reasoning and code generation tasks. Claude is used for analytical writing and document synthesis. Gemini is used for tasks requiring real-time web access. Model selection is driven by task requirements, not vendor preference, and Arcalea's architecture is model-agnostic so systems can be updated as models improve.