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

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

siift

Freemium

An agentic AI operating system that helps founders map, validate and execute business strategy on one intelligent canvas.

Intelligent Business Canvas: A visual workspace that maps ideas, assumptions, actions and results into decision-ready filters so the whole business can be seen at once.
Living Memory System: A scalable agentic memory that learns as the business evolves and keeps context aligned across tools, data and teammates.
AI-Scored Validation: Automated, continuous research that grades assumptions into evidence so founders know what is validated and what is still risky.
Five-Stage Execution Loop: Guided progression through Ideate, Validate, Build, Go To Market and Scale, each with its own AI-driven workflow.
Safe Stack Automations: Human-in-the-loop actions across 80+ popular applications so approved work executes without leaving the canvas.
Shareable Workspaces: Collaborative views that let teammates, advisors and other stakeholders work from the same strategy context.
Proactive Next-Step Guidance: Personalized, iterative advice that surfaces the highest-leverage action rather than a generic checklist.
Credit-Based AI Usage: Monthly request credits scaled by plan and weighted by task complexity, with unlimited projects even on the free tier.

Idea Validation: De-risking a new business concept by turning founder assumptions into automatically researched, scored evidence before building.
Strategy Mapping: Turning a cloud of unstructured ideas into a visual mind-map that exposes blindspots across the business model.
Go-To-Market Planning: Iterating on sales and marketing with an AI-native loop that tests which channels actually produce revenue.
Product Prioritization: Helping product leaders decide what to build next based on verified market opportunities rather than intuition.
Scaling Diagnostics: Systematizing an existing business to surface its current growth constraints and reverse-engineer fixes.
Advisor Collaboration: Sharing a single live strategy workspace with co-founders, advisors and investors instead of static decks.

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.