Skydive, PageIndex, and Caddi: Three Kinds of AI Leverage

This week's shortlist comes from the Product Hunt daily leaderboards for August 27 and 28, 2026. Skydive ranked first on August 27. PageIndex and Caddi ranked first and second on August 28. 12345

They are not three versions of the same product. Skydive is a general-purpose cloud agent that works across company tools. PageIndex is a document retrieval layer for long, complex files. Caddi turns a screenshared process into a governed automation.

The prices and workflows above come from public official pages. They are a useful first-pass buying screen, not a claim that every team's live workspace will behave exactly like the product demo.

Skydive starts with a simple promise: give an agent a name, a role, access to approved tools, and its own computer. The official site says the agent can work through web, Slack, email, or iMessage, keep memory, and run recurring routines after you close your laptop. 13

That makes the first experiment easy to picture. Ask one agent to clear a support queue, prepare a weekly recap, or keep a launch checklist current. The product shows examples across Gmail, GitHub, Notion, Linear, Google Calendar, and many other tools. 7

The setup friction is not the account creation. It is deciding what the agent may do without asking. An agent that can read Gmail, update Linear, change a GitHub issue, and send a Slack message can remove a lot of coordination. It can also make a wrong change in four places before someone notices.

The pricing is unusually clear for a broad agent product. Starter is $20 a month for up to five users. Team is $200 a month with ten times more usage than Starter. Both plans charge usage based on model cost and say they add no markup to that model cost. Enterprise adds SSO, SAML, audit logs, fine-grained security, and custom usage. 6

That gives a small team two separate budget questions. Can the team afford the workspace? And how much work will the agents actually run? The second answer is not in the headline subscription price.

My read is that Skydive has the shortest path from "we keep dropping follow-ups" to "an agent owns this queue." It also has the biggest blast radius. Start with a reversible job, a narrow permission set, and an approval step for anything that sends, spends, deletes, or merges.

PageIndex starts from a different pain. A long financial report, contract, regulatory filing, or technical manual may contain the answer, but a similarity search can return a paragraph that sounds close instead of the passage that actually settles the question.

PageIndex's approach is to build a tree-shaped index and let an LLM reason over that structure. The company describes the result as vectorless, traceable, and grounded in the source document. Its developer materials expose the retrieval layer through an SDK, an API, and MCP. 814

The first useful test is straightforward. Install the SDK, submit one representative document, and ask a question whose answer you can verify by hand. Local mode works on your machine for text-based PDFs. Cloud mode handles OCR, image understanding, and managed storage for scanned or image-heavy documents. 8

That split is the important setup decision. If your documents are clean text PDFs, local mode can keep the data and infrastructure closer to your team. If the corpus contains scans, tables, charts, or a lot of files, cloud mode removes more plumbing but adds a vendor account and a credit meter.

The public developer plans start at a free trial with 200 credits. Standard is $30 a month for 1,000 monthly credits and up to 10,000 active pages. Pro is $50 for 2,000 credits and up to 50,000 active pages. The plan page says indexing costs one credit per page, while the chat layer can use your own LLM and therefore carries the model provider's bill. 9

That is a decent shape for a document-heavy startup. The team can keep the local experiment cheap, then pay for OCR, storage, and scale only when those needs become real. The integration work moves into model keys, document lifecycle, citations, and deciding which answers need a human check.

PageIndex is my pick when the job is due diligence, financial analysis, or answering internal questions from a small set of consequential documents. It is not the pick for a general company assistant. The tool solves retrieval. Your application still has to decide what to do with the answer.

Caddi takes the most operationally specific approach. Its product page asks you to show a repetitive job through a screenshare and conversation. Caddi says it discovers repeated work, learns the steps, builds the automation, and lets leadership govern each run. 15

The first experiment is not "connect everything and see what happens." It is one process that already has a clear owner. Inbox triage, contract filing, client intake, or payment reconciliation are better starting points than a vague request to automate operations.

The setup path is more deliberate than Skydive's. Caddi says IT connects tools over OAuth and SSO in about five minutes. Each user approves access under their own credentials, and Caddi inherits the permissions that user already has. The company also says it keeps an audit trail of API calls and actions. 12

That design cuts one kind of integration pain. You do not have to create a new password vault or invent a separate service account for every workflow. But it creates a different question: whose access should a live automation inherit, and what happens when that person's role changes?

Caddi's free plan is for one user with 200 credits a month and ten active loops. Team costs $250 per user each month and includes 1,000 credits per user plus 20 active loops. Business costs $6,500 a month and adds advanced integrations, SAML SSO, longer history, and a 99 percent uptime SLA. 11

That pricing tells you who Caddi is really for. A solo operator can learn the product without a trial clock. A small team has to believe that the automated work is worth at least $250 per active user each month before the plan becomes comfortable. This is not a cheap general assistant.

Caddi is my pick when a startup has repetitive cross-system work and a real need for reviewable execution. It fits teams that care about permissions, logs, and predictable steps. It is overkill for a one-off task and costly for a team that has not yet found a process that repeats often enough.

If the job is delegating broad coordination across the tools you already use, start with Skydive. Give it one queue, one human reviewer, and one week of reversible work. Measure completed work and cleanup, not the number of actions the agent can technically take.

If the job is getting a defensible answer from a long document, start with PageIndex. Use one real report or contract, bring your own model key, and verify every answer against the cited passage. The point is not that a new retrieval method sounds clever. The point is whether your team can trace an answer quickly enough to trust it.

If the job is turning a repeated back-office routine into a controlled system, look at Caddi. Pick a process with a clear exception path. Show the process once. Then inspect what the automation does when an approval is missing, a document is duplicated, or a permission changes.

So which one deserves a place in a small team's stack? The answer depends on what you are trying to remove. Skydive removes coordination. PageIndex removes the guesswork from finding a passage. Caddi removes the manual steps between systems while keeping a record of what ran.

The launch rankings put these tools beside each other. The buying decision should pull them apart. Choose the narrowest product that fixes the bottleneck you can measure this week.