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compare · Hyperspell vs. 3ngram
Hyperspell is aimed at building a company-wide context graph for teams and agents. If you want your AI work carried forward across Claude, ChatGPT, Cursor, and Codex today, 3ngram is the closer fit.
at a glance · 7 capabilities · side by side
| capability | 3ngram | Hyperspell |
|---|---|---|
| what it is | shared memory and follow-through for AI work | company context graph for agents |
| primary audience | individuals first, teams later | companies and internal agent systems |
| delivery model | typed work memory over MCP same layer across Claude, ChatGPT, Cursor, Codex | filesystem artifacts and synced docs |
| memory model | typed — decisions, commitments, blockers, preferences, patterns | synthesized company context files |
| follow-through | deadlines, stale detection, nudges, autonomous close-the-loop | context delivery only |
| where it works | inside the AI tools you already use | where the synced files are mounted or read |
| maintenance burden | debrief once, reuse everywhere | files and agent instructions can drift across surfaces |
when to choose · Hyperspell
you are building a company context layer for internal agents and want synthesized files or docs that many systems can ingest in a controlled enterprise environment.
when to choose · 3ngram
you want your own AI stack to carry decisions, commitments, blockers, and source context across chat and coding tools without maintaining shared prompt files.