GhostWriter by MyHandler vs Semantica: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of GhostWriter by MyHandler and Semantica — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
GhostWriter by MyHandler
MyHandler.ai
Windows writing assistant that reads the screen around your cursor on a hotkey double-tap and types a context-aware draft in your voice.
Key features
- Hotkey Double-Tap Drafting: No prompt or dictation is needed — a double-tap with the cursor in any text field triggers capture and drafting directly in place.
- Screen Context Capture: Reads the thread, form or partial sentence surrounding the cursor locally on the machine, using that on-screen context as the entire input.
- Writing Intent Classification: Determines whether the moment calls for a reply, a continuation, a filled-in answer or a fresh compose before writing a single word.
- Sender and Identity Mapping: Maps each message in a thread to its sender and works out which handle is the user's, so the draft answers the other party rather than the user's own words.
- Calendar Cross-Check: When a draft proposes a time, it is validated against the next two weeks of a connected calendar before the text appears.
- Selection Rewriting: Selecting existing text before the hotkey rewrites that selection instead of composing something new.
- Nothing Sent Automatically: The generated text appears at the cursor for the user to read, edit or delete; sending always remains a manual step.
- Local Vault with Zero-Retention Cloud: Capture runs against an encrypted vault on the user's own PC and the assembled context is processed by a zero-data-retention cloud model.
Best for
- Email Backlog: Clearing a queue of owed replies by drafting each one from the thread already on screen instead of retyping the same answer.
- Chat and Slack Replies: Answering a message in a team chat where the draft is grounded in who asked whom for what in the visible thread.
- Web Form Completion: Filling a blank answer box under a question on a web form or application without switching to a separate chat window.
- Sentence Continuation: Picking up a half-written paragraph exactly where it stops, without the assistant restating what was already typed.
- Meeting Scheduling Replies: Responding to a request for a time with a proposal that has already been checked against the user's calendar.
- Tone-Sensitive Rewrites: Selecting a blunt or rough draft and having it rewritten in the user's own voice before sending.
S
Semantica
semantica-agi
Open-source, graph-native context and knowledge-graph infrastructure for accountable AI agents in regulated domains.
Key features
- 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.
Best for
- 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.