Heptabase
Visual reading and learning workspace
Heptabase organizes reading notes on visual whiteboards with AI learning features and credit-based plan allowances.
Connected personal knowledge with optional AI
Advisor score
Not yet rated
Research guidance only
The decision
Evaluate with a small public-data pilot before migrating your archive.
Best for
Individuals maintaining personal references.
Choose something else if
Teams needing a governed shared system of record
Evidence
Verified research · rating withheld
Pricing checked
See current vendor pricing · 2026-10-07
No verified permanent free plan is recorded.
Subscription with optional AI add-ons
**Capacities is worth evaluating if you want connected personal knowledge with optional AI assistance.** Its value depends on whether you return to useful notes and maintain them. It is less compelling if your main requirement is a shared team workspace. This is a source-based review; we have not tested the app and withhold numerical ratings.
The [knowledge-base overview](https://capacities.io/ai-knowledge-base) describes pages for projects, people, and other subjects, plus connections between them. It also describes connecting external AI assistants to read and save information in a selected space. This can give a research workflow a persistent home beyond scattered conversations.
The important editorial distinction is between storing an answer and validating it. A saved AI explanation remains a generated claim until its sources and assumptions are checked. Connecting more notes does not turn an incomplete collection into complete evidence.
The [pricing page](https://capacities.io/pricing) shows free Basic and paid Pro and Believer plans. The retrieved table displays Pro at $9.99 per month and Believer from $12.49 per month, alongside monthly/yearly controls; confirm the active billing term at checkout before budgeting. Basic supports core knowledge work, while AI and connectors belong to paid plans.
The [subscription documentation](https://docs.capacities.io/reference/subscriptions) distinguishes the included monthly AI budget from optional Plus add-ons. Top-ups require Plus; usage depends on model, context, and media size. An external assistant’s charges are a separate consideration. Do not interpret access to AI features as unlimited included processing.
Our recommendation is to measure the monthly cost of your normal research routine, including any assistant subscription and extra usage. Budget against useful, checked notes rather than raw message counts.
The [AI privacy documentation](https://docs.capacities.io/more/ai-privacy) distinguishes built-in AI from external connectors. Connected assistants follow their own providers’ privacy terms. The page’s broad no-storage wording also needs to be read alongside its stated limited abuse-monitoring exception of up to thirty days. Verify the applicable provider and settings before sending confidential material.
Begin with a separate evaluation space containing public documents. Where supported, start with read-only access; inspect writes before relying on automatic updates. Keep originals available so a generated rewrite cannot silently replace the evidence you meant to preserve.
The strongest potential benefits are a structured home for notes, links between related subjects, and optional AI assistance near the material being used. These are documented capabilities rather than measured productivity gains.
The main tradeoffs are learning a different organization model, maintaining note quality, variable AI consumption, and a personal-workspace emphasis. A larger collection can require more cleanup and contextual review. Extra AI budget will not solve weak sources or unclear note ownership.
Consider [Heptabase](/tools/heptabase) when visual arrangement is central to thinking. Compare [Reflect](/tools/reflect-open) when a lighter note-taking workflow is the priority. These are differences to test against your own routine, not an independently scored ranking.
Over one week, create a small project space with twenty public notes and several deliberate contradictions. Ask five questions whose answers you can verify manually. Record omissions, correction effort, unexpected access, unwanted edits, and the cost of each session. Restore an earlier note and export a sample before committing your archive.
Then repeat the same work using your existing notes app. Renew only if finding verified information and keeping it current takes less total effort. Use the [Decision Workspace](/decision-workspace) to retain your results.
Personal Recommendation
Evaluate with a small public-data pilot before migrating your archive.
Try the recommendation
Evaluate with a small public-data pilot before migrating your archive.
Evidence status
Rating withheld
Editorial Review Framework
Recommended Because…
Evaluate with a small public-data pilot before migrating your archive.
Research-based guidance is not converted into a numerical rating until a documented evaluation supports the score.
Reusable trial worksheet
Turn this review’s buyer test into evidence. Your entries autosave only in this browser and are never added to shared shortlist links.
Confirm the tool meets every must-have workflow and stakeholder requirement.
Review starting point: Individuals maintaining personal references
Run the same representative work you would use in production; do not score a polished demo.
Review starting point: Complete three to five representative tasks with known acceptable outcomes and compare them with your current process.
Calculate the effective cost per accepted result, including usage, review, corrections, and required add-ons.
Review starting point: The pricing page shows free Basic and paid Pro and Believer plans. The retrieved table displays Pro at $9.99 per month and Believer from $12.49 per month, alongside monthly/yearly controls; confirm the active billing term at checkout before budgeting. Basic supports core knowledge work, while AI and connectors belong to paid plans. The subscription…
Define an acceptance threshold, test known answers and edge cases, and record every correction.
Review starting point: Editorial quality signals: features 0.0/5. Validate these signals in your own work.
Verify what data enters the product, who can access it, how long it is retained, and whether it trains models.
Review starting point: Use approved low-risk data first. Check roles, consent, deletion, subprocessors, model-training settings, and the contract—not only the marketing page.
Test the real handoffs, permissions, failure states, and export path your team depends on.
Review starting point: Capacities integration requirements are not fully structured in this review; list every required system and test each connection.
Record training, governance, reliability, accessibility, ownership, and change-management risks before rollout.
Review starting point: Source quality still requires review; Sensitive content needs policy checks; Migration and export need testing
Loading saved worksheet… · private to this device or your optional account
Evaluation
Research-based
Price posture
freemium
Reviewed
2026-10-07
No authentic product screenshot is published for this review. DiscoverAI does not use generated interface images as product evidence.
Editorial freshness
Confirm billing and entitlements at current checkout.
Community evidence
Structured, editor-moderated experience—not star ratings. This complements our independent review and never changes its score.
No approved community evidence yet. Be the first verified user to contribute.
Basic is the free core product; check Pro entitlements for AI and connectors.
No. Included budgets, Plus add-ons, and eligible top-ups are separate.
The product overview says external assistant chats do not use the Capacities AI budget; external provider charges still matter.
No. This is a source-based review with numerical ratings withheld.
Its personal-workspace focus makes shared organizational requirements a separate evaluation.
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