The words founders Google before they buy.

A whole business function (Sales, Content, Ops, Support) operated for you by AI agents on a monthly retainer, instead of being built with a salary stack.

A part-time Chief AI Officer engagement that gives funded teams strategic AI direction without the cost of a full-time executive hire.

A part-time Chief Marketing Officer on retainer who runs strategy without taking a permanent seat, often paired with an AI Content Department for execution.

A part-time COO on retainer who gives funded teams the operations leadership they need without the cost of a full-time C-suite hire.

Cold outbound (email, LinkedIn, sometimes voice) where an AI agent handles every step from prospect research through follow-up, with a human on the warm-reply handoff.

An AI agent that handles SDR work end to end: sourcing, enrichment, personalization, sequencing, and follow-up until a prospect replies.

The discipline of getting cold outbound emails into the inbox, not the spam folder. Covers domain warming, sending volume caps, reputation, and spam-trap monitoring.

Gradually building sending volume on a new domain over weeks so spam filters trust it. Required before any meaningful cold outbound from a fresh domain.

Behavioral signals indicating a prospect is in-market for a solution. Sources include website visits, search behavior, content downloads, and third-party providers.

The process of attaching additional context (firmographic, demographic, technographic, behavioral) to a raw lead so outreach can be relevant.

Tools that identify anonymous B2B visitors to a website by company and sometimes person, so outbound can target real intent signals.

The percentage of cold outbound emails that get a reply, positive or negative. Honest industry rate is 1-2%; AI-personalized cadences run 4-6%.

The schedule and channel mix of an outbound sequence: which messages go out on which days, mixing email, LinkedIn, and occasionally voice.

A positive response from a prospect to outbound that is qualified enough to hand off to a human rep for a discovery call.

A continuously running content production layer (articles, social, landing pages, email) operated by AI agents on a single retainer, instead of a marketing team plus an agency.

Google AI-generated summary at the top of search results, citing a few sources. Being cited drives high-quality traffic; not being cited reduces clicks.

An automated workflow that drafts, schedules, and publishes social content (LinkedIn, X, Instagram) on cadence, with the founder approving in minutes rather than writing from scratch.

An AI writing model fine-tuned or prompt-tuned against a brand existing copy so output preserves voice, style, and positioning at scale.

Google framework for evaluating content quality across Experience, Expertise, Authoritativeness, and Trustworthiness. Higher E-E-A-T pages rank better.

Producing hundreds or thousands of search-targeted pages by combining a content template with data inputs, so each page targets a long-tail query.

Machine-readable metadata that tells search engines what a page is (Article, Service, FAQ, Product). Powers rich results and AI Overview citations.

An automated reporting workflow that pulls source data (Stripe, HubSpot, Notion, banking), refreshes live dashboards, and drafts the narrative for board updates without the COO stitching it on Sunday.

AI-generated written commentary attached to a dashboard or board update that explains what numbers moved, why, and what to do about it.

Percentage of customers or revenue lost over a period. The most important SaaS metric most ops teams cannot calculate accurately.

MRR sliced by acquisition cohort (signup month or quarter) so each cohort retention and expansion can be measured against others. Foundational SaaS ops metric.

The inevitable end state of every dashboarding tool deployed without a function to own it. Looker, Tableau, Metabase boards drift out of date within a quarter and nobody trusts them.

An AI agent trained on a company internal knowledge (wiki, Notion, Drive, Slack history) that answers tier-1 internal questions so engineers and operators are not the help desk.

Lifetime value of a customer divided by cost to acquire them. Healthy SaaS is 3:1 or higher with sub-12-month payback.

Revenue from a cohort of customers a year later divided by their original revenue, including expansion. Above 110% is good SaaS; above 130% is exceptional.

A prospect who has demonstrated value-realizing behavior inside a product (key actions, usage thresholds) and is therefore qualified for sales contact based on usage rather than firmographic fit.

An AI agent trained on a company knowledge base, product docs, and policies that handles routine support questions without human involvement.

Scoring customer accounts on probability of cancellation using usage signals, ticket sentiment, engagement drops, and billing events so the team can intervene early.

An AI agent ingested with a company documentation, help articles, and historical support transcripts so its answers stay grounded in actual product behavior.

Customer support inside a SaaS context where every ticket carries account-specific context (plan tier, integrations enabled, API behavior, admin permissions) that must be read before responding.

Training an existing AI model further on a specific dataset to specialize it for a domain. Used for brand voice, internal copilots, and domain-specific tasks.

A large language model deployed on private hardware (Llama 3, Qwen, Mistral) rather than accessed via a hosted API like OpenAI or Anthropic.

An AI agent running on hardware controlled by the buyer (on-prem server, local workstation, isolated VM) with no inference traffic leaving the network.

AI technique where the model retrieves relevant context from a document store before generating, so answers stay grounded in your data instead of hallucinating.

Contract between a data controller and processor required under GDPR. Defines scope, security measures, subprocessors, and liability.

EU regulation on personal data. Requires lawful basis for processing, data subject rights, breach notification, and DPO appointment for larger processors.

AI agents configured for healthcare workloads where PHI is involved, requiring a signed BAA, sometimes on-device deployment, and clinician escalation guardrails.

AI agents that handle Know Your Customer and Anti Money Laundering workflows for regulated financial businesses, often deployed on-device to keep customer PII inside the perimeter.

AICPA audit framework covering security, availability, processing integrity, confidentiality, and privacy. Enterprise SaaS sales gate.

EOI standard fractional engagement starting cadence. Days 1-3 audit, 4-10 build, 11-14 handoff. By end of week 4 the department is operating autonomously.

A half-day workshop and written roadmap that maps a company AI opportunities to its stack, team, and goals with prioritized recommendations.