GTM teams drown in disconnected signals — G2 reviews, job boards, LinkedIn noise. Vx Context Studio turns that raw mess into a living Knowledge Graph your AI agents can query and act on — right inside the tools you already use.
Buying intent is everywhere — scattered across reviews, LinkedIn posts, and job boards. A flat CRM table treats all of it as disconnected strings of text. So you're left choosing between two broken paths.
When a company posts an angry review about a competitor's API limits, that's a live buying signal. But a flat CRM table is completely blind to the relational web of intent hiding inside unstructured text.
Buy 10,000 leads and spray them — you burn your domain at a 1% reply rate. Or spend eight hours manually researching ten accounts. Neither approach works. There's no third path.
Every enrichment platform silos your data. When you stop paying, the intelligence disappears. You're renting insight at a monthly rate, not building an asset that compounds.
Every GTM motion runs on context. Vx Context Studio captures six signal layers across your entire market — so when the moment comes, your team already knows everything they need to act.
Firmographic foundation — org structure, headcount, funding stage, and industry. Every account starts as a rich, connected profile, not a flat row.
Behavioral signals that reveal where a buyer is in their journey — content consumption, community discussions, and engagement activity that flag an active evaluation.
Tools in use, API activity, stack changes, and integration patterns. Know what a company has deployed — and where the opportunity gaps are.
Calls, emails, and meetings — with extracted sentiment, objections raised, and follow-up commitments. Every conversation enriches what's known about the account.
Web visits, email opens, and campaign responses — mapped against time to reveal momentum and intent velocity, not just isolated activity.
Deal stage history, relationship mapping, and closed-lost reasons — all connected to the same intelligence layer as your live signals, so nothing lives in isolation.
Data flows through 4 layers — bottom up — turning scattered signals into a flawless outbound campaign.
Scraped job boards, competitor reviews, raw data logs — unformatted and uncleaned. You dump it straight into your database staging tables.
input layerThe Vx semantic engine extracts key entities — companies, competitors, tools, pain points — and weaves them into interconnected graph nodes. Text becomes meaning.
semantic engineYour active Playbooks inject strategic guardrails — competitive battlecards, tone-of-voice, displacement guidelines — directly into the AI's runtime context at query time.
playbook engineThe AI agent reads the graph over MCP, verifies facts against live tables, respects human-in-the-loop write permissions, and streams out hyper-contextual campaigns instantly.
execution layerEach layer is a focused, single-responsibility module. Here's exactly what each one does — and why it matters for GTM.
You dump raw, unformatted data into your database staging tables. You don't need to clean it. The Vx semantic engine automatically extracts key entities — companies, competitors, tools, and specific pain points — and records them as interconnected nodes. It turns text into meaning.
Semantic EngineThe system monitors how recently a connection was spotted. When a competitor pain point flares up, the graph automatically applies a dynamic curation label — like hot_lead or churn_risk. Signals that are 2 hours old rank above signals that are 2 months old. Your data scales and refines itself over time.
You control how the AI thinks without writing a single line of code. Your product marketing team can update competitive battlecards, tone-of-voice rules, and displacement guidelines directly in the control panel. These Playbooks are injected straight into the AI's system prompt at runtime — giving you strategic control over every generated output.
Playbook EngineYour growth engineers pull up their preferred AI assistant and work natively — no new browser tabs. Because Vx acts as a standardized MCP tool server, the AI agent can safely query the graph, verify facts against live tables, respect human-in-the-loop write permissions, and stream out hyper-contextual campaigns instantly.
Execution LayerA single Growth Engineer sits in their AI assistant. No extra tabs. No dashboard. One natural-language query — and Vx Context Studio handles the entire research, personalization, and outbound draft.
Signal detected: Acme Corp posts an angry review about a competitor's API limits. Vx ingests it and tags the graph node hot_displacement_lead automatically.
Playbook resolved: The directive engine matches the Displacement Battlecard and injects it into the AI's system prompt — no manual intervention needed.
Pitch drafted: The AI queries the Knowledge Graph, pulls live context on Acme Corp, and writes a hyper-personalized pitch emphasizing your API reliability and uptime SLA.
Human approval gate: The draft surfaces to the operator for review before anything is sent. Full strategic control, zero manual research.
By decoupling the intelligence layer from a rigid frontend UI, your organization unlocks true GTM leverage that compounds over time.
A single growth operator can execute the strategic prospecting, research, and hyper-tailored personalization work of an entire 5-person outbound agency — volume without spam, precision without hours of manual research.
Every time your system ingests market signals, your internal Knowledge Graph grows smarter. You aren't renting data from external platforms — you are building an appreciating enterprise asset that no competitor can buy away from you.
No new browser tabs to open. No training sessions on a new software interface. The context engine hooks directly into the tools your technical operators are already using to build the company.
We're onboarding a limited number of GTM teams onto the beta. Leave your details and we'll be in touch. Beta
Compatible with any MCP-enabled AI assistant