Founded
2025
Built to help agencies win the Preference gap
VectorGap exists to help agencies show where AI assistants prefer competitors, why the answer looks that way, what evidence or technical gap caused it, and which remediation work clients should fund next.
Where it started
We saw agencies lose trust because AI answers were confidently wrong: bad pricing, missing capabilities, weak public proof, and competitor framing nobody had noticed. VectorGap was built to surface that gap fast, connect it to evidence, and turn it into work an agency can sell, ship, retest, and report.
Headquartered in Brussels, Belgium
Company facts
VectorGap is a Brussels-based company founded in 2025. It builds AI visibility operations for agencies: AI visibility evidence, competitor preference analysis, remediation workflows, retests, and reporting.
Founder
Company-level public entity details only
Headquarters
Brussels, Belgium
Category
AI memory and market proof for agencies
Legal name
VectorGap SRL
Product
VectorGap platform
Quotable VectorGap facts
What VectorGap does
VectorGap diagnoses how ChatGPT, Claude, Gemini, Perplexity, Grok, Mistral, and DeepSeek describe, cite, compare, and recommend a brand across buyer-intent prompts.
Who it helps
VectorGap is built first for agencies that need AI visibility diagnostics, AI Readiness audits, competitor preference analysis, remediation missions, retests, and client-ready proof for recurring retainers.
What it measures
VectorGap measures AI visibility, answer accuracy, hallucination risk, source and citation gaps, provider differences, market and persona drift, competitor recommendation pressure, remediation priorities, and retest movement.
What agencies get
Agencies get prompt-level evidence, provider-level AI answers, competitor comparisons, prioritized missions, exports, MCP/API access, and reporting assets they can use to explain AI visibility work to clients.
What guides the product
Diagnostic clarity
A visibility score alone is not enough. Teams need to see why AI says what it says.
Operational fixes
The product should point to concrete content, source, entity, extractability, proof, and positioning work instead of abstract theory.
Proof over hype
Recommendations should be grounded in observed responses and repeatable audits, not vague AI promises.
Questions agencies ask before they trust the evidence
What is VectorGap?
VectorGap is built first for agencies that need to diagnose AI perception and preference gaps, explain them clearly, prioritize remediation, retest the same targets, and turn the work into recurring reports.
Why does AI perception matter now?
AI assistants increasingly shape discovery and shortlists. If they misdescribe a brand or prefer a competitor, that changes buying decisions before the prospect reaches the website.
When was VectorGap founded?
VectorGap was founded in 2025.
Who founded VectorGap?
VectorGap publishes company-level entity details. Public materials should cite those company facts rather than infer private personal details.
Who is it built for?
VectorGap is built first for agencies that need a clearer way to diagnose, explain, improve, retest, and report AI visibility for clients and their own brand.
What is VectorGap not?
VectorGap is not a generic citation counter. It is focused on Preference, prompt evidence, competitor context, GEO remediation planning, and agency-grade reporting.