Jottoo vs Thinking Orbs: Features, Pricing & Which Is Better (2026)

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

Jottoo

Paid

AI meeting workspace that records and transcribes conversations, summarises decisions, and turns follow-ups into tracked tasks.

Flexible Capture: Record a meeting live, upload an existing audio file, or type a note directly — every input lands in the same workspace.
Searchable Transcripts: Conversations are transcribed into full text you can search after the fact, so you do not have to take notes during the meeting.
Instant Summaries: Each meeting is condensed into key decisions and highlights, so you get the outcome without rereading the whole transcript.
Action Items to Tasks: Follow-ups surfaced from a conversation convert into actionable tasks with deadlines and are managed alongside your other work.
Smart Folders and Notes: Meetings, notes, and folders are organised in one workspace with a recent-meetings view and a unified task list.
Calendar Workflow: Meetings and the tasks they generate connect to your calendar so scheduled work and follow-ups stay in one flow.
Offline-Friendly Notes: Notes stay openable and editable when the network drops and sync back once you are online again.
Privacy-First Data Handling: Encrypted sync for sensitive note content, minimal data sharing, no advertising model, and transcription providers used only while those features run.

Bot-Free Meeting Capture: Recording client or internal calls without adding a visible note-taking bot to the participant list.
Decision Recall: Pulling the agreed decisions out of a long meeting weeks later without rewatching or rereading anything.
Follow-Up Tracking: Turning the 'I'll send that over by Friday' moments of a call into dated tasks that do not get lost.
Field and Offline Notes: Taking notes on unreliable connections and letting them sync when the network returns.
Privacy-Sensitive Conversations: Recording discussions where encrypted sync and a no-ads business model matter more than integrations.
Solo Operator Admin: Running meetings, notes, tasks, and calendar from one workspace instead of stitching together a transcriber and a task app.

Yogesh

Free

Thinking Orbs is a lightweight React library of animated orb status indicators for AI interfaces such as thinking, searching and compacting.

State-Based Orbs: An Orb component with states like reasoning, searching, working, retrying, compacting and waiting to mirror what the agent is doing.
Zero Dependencies: The React orb needs nothing but React and the plain JS version needs nothing at all, at about 3.8 KB gzipped.
Customizable Props: Control variant, size, speed, density, dot size, tilt, pause and screen-reader label to fit any interface.
Opt-in Shapes and Renders: Import extra shapes like cube and renders like halftone separately so only used code is bundled.
Flexible Installation: Install from npm, pnpm, yarn or bun, or copy the component into a project with shadcn.
Tintable with CSS: Color orbs with text-* utility classes so they match the host UI theme.
Interactive Playground: A web playground to preview all states, shapes and renders before integrating.
llms.txt Support: Publishes an llms.txt so coding assistants can integrate the library correctly.

Chat Interface Status: Show a thinking or reasoning animation while an LLM responds.
Agent Progress Display: Indicate searching, working or background-task states in an agentic coding UI.
Context Compaction Feedback: Visualize compacting states when conversation history is summarized.
Retry and Waiting States: Signal retries or waiting-for-input states with distinct orb variants.
Design System Components: Add a polished AI loading indicator to an in-house React component library.
Prototype AI Products: Quickly drop a refined status animation into demos and prototypes.