Workspace context
Brands, competitors, markets, personas, audit presets, knowledge facts, and reports stay attached to the correct workspace context.
Trust layer
Trust starts with evidence the agency can inspect, export, and explain.
VectorGap is built for agency teams that need client-ready AI visibility evidence, careful claims, exportable reports, and a reproducible audit workflow rather than unsupported visibility promises.
What the buyer can verify
Audit evidence stays tied to prompt, provider, answer, source, market, persona, and competitor context.
Reports and exports help agencies own the client conversation.
API and MCP workflows support advanced agency reporting and automation.
Provider variability is documented instead of hidden.
6
standard providers
98
LLM prompts
40
AI Preference prompts
Data handling
Built for agency workspaces and client reporting
Agencies need to separate client records, export evidence, and explain methodology. VectorGap keeps audit context and report outputs structured so teams can manage client portfolios without losing the evidence trail.
Report ownership
Agencies can use exported reports and summaries to explain AI visibility findings in client conversations.
Sensitive examples
Public examples use anonymized brand, competitor, and prompt labels. Private workspace results should be handled as client data.
Reproducibility
AI answers change, so the workflow must be repeatable
VectorGap does not pretend AI outputs are static. It preserves target context and uses retests to compare movement across the same providers, markets, personas, and competitors.
Provider caveats
Different providers can disagree. That disagreement is useful evidence when diagnosing source coverage and entity clarity.
Retest discipline
Progress reports should compare the same audit targets after remediation work, not random new prompts.
Exportable evidence
CSV, Markdown, PDF, API, and MCP paths help agencies move evidence into reports, dashboards, and operating workflows.