Enterprise Sales Knowledge Graph & MCP Server
The BRAIN that powers successful agentic AI initiatives.
Your reps are already using AI for deal questions. The issue is what that AI is working from — one transcript, maybe some CRM fields. We give it the full picture: methodology, evidence, history, patterns.
Grounded Answers, Not Generated Guesses
|
Large number of questions + many unstructured sources (transcripts, emails, WWW) + complex concepts drive severe accuracy issues. No practical way to validate the outputs at scale.
Predictable Outputs, Not Iteration Loops
|
LLM outputs are inconsistent and may require numerous iterations — which is an adoption killer for sales teams.
Your Methodology and History, Enforced
|
Every industry, organization and deal has historic context that impact decisions. Ignoring that is like hiring a college student.
Built-In Feedback and Learning
|
LLMs don't analyze and incorporate learnings automatically so there is no ongoing improvement mechanism.
Cost Control at Scale
|
Cascading agents drive out of control tokens cost. While insufficient at a small scale, any deployment at scale must take cost into consideration.
Three Layers of Intelligence
40M+ signals. Three layers of learning. Built on $8B+ in managed pipeline.
Unique Enterprise Value-Sales Structure
Unique Enterprise Value-Sales Structure
Semantic structure of pre-learned entities & relations for enterprise sales driven by hundreds of sales leaders and CROs across every major B2B vertical.
$8B+
Pipeline managed
Layered Learning
|
Enterprise sales layer
|
Industry knowledge layer
|
Customer-specific playbook & interactions
|
Winning and losing patterns
Perfecting signals across all customers, industries and privately per-customer
210K
Contacts qualified
De-Construction of Complex Concepts
De-Construction of Complex Concepts
Complex concepts broken down to millions of atomic AI-signals that are matched, scored and rolled back up to decisions. No single LLM prompt can replicate this.
40M+
Signals and growing
Model Context Protocol
MCP: Plug the Brain Into Your Stack
MCP: Plug the Brain Into Your Stack
Your reps are already using AI to ask deal questions. The issue is what that AI is working from. Spotlight.ai's MCP Server connects any AI tool to the Knowledge Graph — so the answers are grounded, methodology-aware, and evidence-backed.
Zero Workflow Disruption
06
Reps keep using whatever AI tool they're already using. The MCP plugs in underneath. The intelligence improves; the habit doesn't change.
Cross-Deal Intelligence
05
Scoring and gap signals informed by patterns across millions of sales interactions. What actually predicts wins, at scale — not one
team's guesses.
Evidence Quality Scoring
04
Every data point tagged by source: confirmed in conversation, manually logged by rep, or calculated from signals. AI that knows the difference between fact and assumption.
Evidence-Grounded Retrieval
03
The AI retrieves structured, validated data. It doesn't invent. When data is missing, it surfaces as a visible gap — not a confident wrong answer.
Methodology Enforcement
02
Your company's specific MEDDICC playbook, codified — what's required, what's blocking, what the failure criteria are at each stage.
Longitudinal Deal Memory
01
Every call, email, and CRM touchpoint over the full deal lifetime — not just the last transcript. Ask "who's my champion?" and get an answer built on everything.
Q
How is this different from CRM AI?
CRM AI queries structured fields — stage, amount, close date. Spotlight queries evidence from actual conversations, MEDDICC completion, scored gaps, and deal risk signals derived from millions of outcomes. The CRM knows what reps typed. We know what was actually said.
Q
Can't we just upload transcripts and prompt our way to deal intelligence?
One transcript equals one moment. No deal history, no cross-deal awareness, no methodology enforcement. AI will fill in missing answers with plausible-sounding guesses you can't catch. That's fine for drafting emails. Not for deal coaching on a $200K opportunity. Evidence quality — knowing whether data was confirmed in conversation or typed into a CRM field — is an architecture problem, not a prompt problem.
Q
Why can't I build my own enterprise sales knowledge graph?
You'd need millions of cross-company data points to establish winning patterns. Spotlight.ai's Knowledge Graph is built on 40M+ signals from $8B+ in managed pipeline across hundreds of CROs and every major B2B vertical. Your pipeline alone doesn't have the volume to train the patterns that predict wins at scale.
Two Ways In
Powered by the Spotlight.ai Knowledge Graph Brain — whether you use the full platform or connect your own agents.
Compatible with
Meet Your Elite Agent Squad:
AI Specialists Working 24/7
Each agent has a unique personality and expertise - together they automate your entire revenue operation .
Analytics Agent
Real-time dashboards & adoption insights. Measures impact, usage, forecast accuracy, rep performance, and ROI.
Research Agent
.png)
Account intelligence: news, M&A,
org moves, competitor signals, benchmarks. Connects external data with internal opportunity context.
Inspection Agent
.png)
Autonomous deal inspection & bottom-up forecasting. Highlights fact vs. opinion, slippage risk, and win/loss patterns.
.png)
Discovery Agent
Captures every conversation: calls, emails, Slack, meetings.
Extracts signals, risks, and actions — privacy-aware and channel-agnostic.
Debrief Agent
Autonomously creates summaries, follow-ups, and next-step mentoring.
Updates CRM with outcomes and prep for next meetings.
Qualification Agent
.png)
Deep MEDDPICC deal evaluation.
Scores Champions, Economic Buyers, metrics, and risk factors.
