Salesforce AI Glossary
Plain-language definitions of the Salesforce, AI, and B2B-sales terms you'll encounter while evaluating Salesforce AI platforms — written by the GPTfy team.
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5 termsAI Agent → Agentic AI
- AI AgentA software entity that takes goal-directed actions autonomously, calling tools, retrieving data, and producing outcomes without step-by-step human guidance.
- AI GovernanceAI governance is the framework of policies, processes, and controls that ensures AI systems are approved, deployed, monitored, and used responsibly.
- AI GuardrailsAI guardrails are policy-enforcing checks that filter LLM inputs and outputs to block unsafe, off-policy, or non-compliant AI behavior.
- AgentforceSalesforce's autonomous AI agent platform, launched in 2024 on the Atlas Reasoning Engine, taking actions across Sales, Service, and other Salesforce Clouds.
- Agentic AIAI systems that autonomously pursue goals using tool calls and multi-step reasoning — distinct from generative AI (which produces content) or predictive AI.
3 termsB2B Sales → BYOM (Bring Your Own Model)
- B2B SalesBusiness-to-business sales — selling to other organizations, typically with multi-stakeholder buying committees, long cycles, and consultative methodologies.
- BANTA sales-qualification framework (Budget, Authority, Need, Timing) developed by IBM in the 1960s and still used to assess whether a B2B lead is worth pursuing.
- BYOM (Bring Your Own Model)An architecture letting enterprises plug their preferred LLM (Claude, GPT-4, Gemini, Llama) into Salesforce instead of being locked to the vendor's default.
3 termsCPQ (Configure, Price, Quote) → Conversation Intelligence
- CPQ (Configure, Price, Quote)Salesforce's quote-generation tool — reps assemble configurations, apply pricing rules, route approvals, and generate proposals, now increasingly AI-driven.
- Context WindowThe maximum amount of text (measured in tokens) an LLM can process in a single request — covering both the prompt and the response.
- Conversation IntelligenceAI analysis of sales and service calls — transcription, sentiment, topic extraction, and coaching insights generated automatically from recordings.
2 termsData Cloud → Data Residency
- Data CloudSalesforce Data Cloud (now Data 360) is Salesforce's real-time CDP and data layer that unifies customer data into one profile to power AI.
- Data ResidencyData residency is the requirement that data, including AI prompts and outputs, be stored and processed only within a specific geographic region.
3 termsEinstein (Salesforce Einstein AI) → Embeddings
- Einstein (Salesforce Einstein AI)Salesforce's native AI platform (launched 2016) providing predictive scoring, chatbots, and generative AI across Sales, Service, and Marketing Clouds.
- Einstein Trust LayerSalesforce's LLM security abstraction — masks PII before sending to AI models, audits every prompt and response, and blocks training on customer data.
- EmbeddingsNumeric vector representations of text that capture semantic meaning — the foundation of semantic search, RAG, and most modern NLP applications.
2 termsFine-Tuning → Function Calling
2 termsGenerative AI → Grounding
- Generative AIAI systems that produce new content — text, images, code, audio — rather than just classifying or predicting from existing data.
- GroundingSupplying an LLM with authoritative, current, customer-specific data inside the prompt so its response is anchored in real information, not training data.
3 termsLLM (Large Language Model) → Lead Scoring
- LLM (Large Language Model)A neural network trained on massive text corpora to predict and generate text — the foundation behind ChatGPT, Claude, Gemini, and modern AI assistants.
- Lead RoutingThe process of automatically assigning incoming leads to the right sales rep based on rules (territory, industry, deal size) or AI-driven matching.
- Lead ScoringAssigning a numeric value to a lead that predicts conversion likelihood — historically rule-based, increasingly driven by ML models trained on past conversions.
5 termsMCP (Model Context Protocol) → Multi-Agent Orchestration
- MCP (Model Context Protocol)An open protocol from Anthropic (late 2024) for connecting AI models to external tools and data sources in a standardized way — like USB-C for AI.
- MEDDICA B2B sales-qualification methodology (Metrics, Economic Buyer, Decision Criteria, Decision Process, Identify Pain, Champion) developed at PTC in the 1990s.
- MEDDPICCAn extended version of MEDDIC adding Paper Process (legal/procurement) and Competition — used in enterprise SaaS and complex deals.
- Model RoutingModel routing sends each LLM request to the best-fit model based on task complexity, cost, latency, and quality instead of a fixed default.
- Multi-Agent OrchestrationA pattern where multiple AI agents — each with specialized roles and tools — collaborate to complete a task, coordinated by an orchestrator agent or framework.
4 termsPII Masking → Prompt Injection
- PII MaskingDetecting and redacting personally identifiable information (names, emails, SSNs) from text before sending to an external LLM, then restoring in the response.
- Prompt Builder (Salesforce)Salesforce's no-code tool for designing, testing, and managing prompt templates that connect records to LLMs — core to the Einstein generative AI stack.
- Prompt EngineeringDesigning instructions, examples, and context to get the best output from an LLM — the art and science of "talking to AI" effectively.
- Prompt InjectionPrompt injection is an attack that hides malicious instructions inside text an AI reads, tricking the model into ignoring its rules.
4 termsSales Cloud → Semantic Search
- Sales CloudSalesforce's flagship sales-focused CRM product — manages leads, accounts, opportunities, and the sales pipeline; the most widely deployed Salesforce module.
- Sales EnablementEquipping sales teams with the content, tools, training, and information they need to sell effectively — increasingly AI-augmented and automated.
- Sales ForecastingPredicting future revenue from pipeline data, historical close rates, and (increasingly) AI signals — used for capacity planning, reporting, and goal-setting.
- Semantic SearchSemantic search finds records and content by meaning rather than exact keywords, using vector embeddings to match intent.
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