Semantica vs Visiby: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Semantica and Visiby — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Semantica

semantica-agi

Free

Open-source, graph-native context and knowledge-graph infrastructure for accountable AI agents in regulated domains.

Graph-Native Ingestion: Ingest enterprise data and extract entities, relationships, and provenance into a Context Graph plus a formal Knowledge Graph.
Polyglot Graph Storage: Native support for both RDF and Labeled Property Graphs so you can pick the model that fits each domain.
W3C Standards & Interoperability: SPARQL, OWL, and related standards keep the graph portable across tooling with zero vendor lock-in.
Deterministic Reasoning: Rule-based and causal reasoning over the graph so agent decisions are reproducible, not black-box.
Decision Provenance: Every decision is traceable back to the ingested evidence and the reasoning steps that produced it.
Ontology & Knowledge Modeling: First-class tools for defining, evolving, and enforcing the domain ontology that governs agent context.
Self-Hostable: Deploy the whole stack inside your own infrastructure — the code is MIT-licensed and open.
Regulated-Domain Ready: Built for high-stakes, governed use cases where auditability and end-to-end traceability are mandatory.

Auditable Agent Decisions: Build agents in finance, healthcare, or public sector where every decision must be traceable to source data.
Enterprise Context Management: Turn scattered enterprise data into a queryable Context Graph the agent uses as its long-term memory.
Causal Analysis: Run causal reasoning over the graph to explain outcomes, not just correlations.
Ontology-Driven Extraction: Enforce a domain ontology so extracted entities and relationships remain consistent across sources.
Regulated Deployment: Self-host in a compliance-bounded environment with zero third-party data egress.
Knowledge Graph Bootstrapping: Ingest documents, databases, and events into a formal KG that agents and BI tools share.

FNA Technology

Paid

AI visibility platform that tracks how ChatGPT, Perplexity, Claude, Gemini and AI Overviews cite your brand, and ships fixes.

AI Citation Tracking: Continuously samples roughly 50,000 prompts per week across ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews to record where and how a brand is cited.
Per-Engine Visibility Scoring: Reports a composite AI Visibility score plus share of voice and prompts won or lost, broken out engine by engine so declines can be traced to a specific model.
Prompts & Citations Explorer: Lets teams open any tracked prompt and read the actual model answer to see which competitor was named and why.
Brand Entity Analysis: Maps the adjectives each engine associates with your brand versus competitors and suggests reframing plays to change that portrait.
Competitor Intelligence: Tracks rival citation share on comparison and 'alternatives to' prompts, highlighting categories where a competitor dominates.
Prioritized Action Plan: Converts findings into P0/P1 recommendations such as schema additions or comparison pages, each with a time estimate and projected score gain.
Site Audit for AI Parseability: Audits pages for missing entity definitions, structured Q&A data and other signals that prevent models from citing the site correctly.
White-Label Reporting and API: Higher tiers add white-label client reports, SSO/SAML and API access for agencies managing multiple brands.

AI Search Monitoring: Marketing teams track whether ChatGPT and Perplexity recommend their product or a competitor on high-intent category prompts.
Competitive Benchmarking: Brands quantify how much citation share a named rival is capturing on 'alternatives to' and 'best of' queries.
Content Prioritization: Content teams decide which pages to write or refresh based on which prompts are currently missed rather than on keyword volume alone.
Technical AEO Audits: SEO specialists find pages lacking FAQ schema or entity markers that keep answer engines from parsing them.
Agency Client Reporting: Agencies run pooled prompt tracking across multiple client workspaces and deliver white-label AI visibility reports.
Executive Reporting: Operators present a weekly digest showing search clicks alongside AI citation share to explain traffic shifts leadership sees.