AI Assist
Freemium
Users prioritizing on-device processing and data privacy
Every time you start a new chat in a different AI tool, you re-explain the project — the stack, the constraints, the decisions already made — because nothing carries over.
$19/month or $190/year · Free tier: One memory across models, 50 Inkfold-managed messages a month (planned), 90-day history, 2 devices, 1 gigabyte storage · Checked Oct 21, 2026
Inkfold sits between you and your AI subscriptions, indexing conversation history across ChatGPT, Claude, Gemini, Grok, and others, then injecting the relevant context when you open a new chat on any vendor. The core workflow is capture-remember-inject: import existing chats, let the tool extract entities and decisions, then route new queries through whichever model fits the task with your memory already attached. It works well for solo power users who juggle multiple subscriptions and lose context at every vendor boundary. The ceiling appears fast for teams: shared memory and the admin console are paid-only features, and the product is still in private alpha — so the reliability guarantees you need before connecting production workflows do not yet exist in public form.
Bottom line: Pick Inkfold if you pay for three or four AI subscriptions and spend real time re-establishing project context on each one — skip it if you need auditable, SLA-backed memory for a team workflow that cannot tolerate alpha-stage breakage.
Getting started tier
For individuals
For teams, $32 per seat per month
First 20 people, price locked while subscribed
View full pricing on inkfold.app →
Pricing may have changed since last verified. Check the official site for current plans.
Find your fit
More options in Productivity. Compare pricing, platforms, and features side by side.
Freemium
Users prioritizing on-device processing and data privacy
Free
Users seeking culturally grounded AI responses
Switching between AI vendors means starting cold every time — no memory of the codebase decisions, the client preferences, the thread you were pulling last week. Inkfold addresses that by acting as a shared memory layer across vendors. You connect your existing tools, import past conversations, and then route new chats through Inkfold’s web app, CLI, or mobile app. At each turn, it extracts entities, decisions, and preferences from the conversation and adds them to a structured context store. When you open a chat — whether on Claude, GPT-5, Gemini, or a locally-run Ollama model — Inkfold injects the relevant signal before the first token fires.
The differentiating architecture is the three-layer signal stack the vendor describes: your personal history, topic-level patterns, and a crowd-sourced domain signal that the platform calls FusionLayer. The claim is that context sharpens over time rather than growing stale or bloated. Privacy tiers add specificity: Smart retention indexes conversations for full context quality, Private mode applies end-to-end encryption with opaque nodes so even Inkfold cannot read the content, and an Incognito mode captures nothing. Bring-your-own-key support means you can route queries through your own API credentials for every major vendor instead of consuming Inkfold-managed message credits.
The tool fits individual power users who maintain parallel AI subscriptions and need continuity across them without copy-pasting context manually. Teams get shared memory and an admin console, but those features are paid-only, and the product is currently in private alpha — meaning access is gated, the feature set is still solidifying, and production-grade SLAs are available only through a custom enterprise conversation. Organizations that need custom data residency or compliance controls are directed to contact the vendor directly; no self-hosted deployment path is documented on the public page.
On the integration side, the vendor lists supported import sources as ChatGPT, Claude, DeepSeek, Gemini, Grok, and Perplexity, and lists supported models including Claude Haiku, Sonnet, and Opus; GPT-5 and GPT-5 nano; Gemini 2.5 Pro and Flash; DeepSeek R1; Grok; Llama 3.3 via Ollama; Mistral; and Qwen 2.5. There is no API surface documented for external integration, so teams cannot wire Inkfold memory into their own tooling programmatically.
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