Import.io
Managed web data extraction, pipelines, quality controls, and delivery
The visible enterprise web data loop is buildable, but a credible replacement needs more than the first screen. Import.io earns its keep through connectors, auth, reliability, so expect a weekend or multi-day build and a narrower personal scope.
Build verification: not recorded. How we judge buildability
What you give up
- hundreds of maintained connectors
- OAuth app verification
- durable execution at scale
- schema drift handling and enterprise controls
Why people still pay
Import.io: One automation is easy. Subscribers pay for maintained integrations, credentials, retries, observability, and someone else owning breakage.
Your build guide
The stack, security requirements, and agent rules for a focused replacement.
Before you start
- Runtime and tools: Python, HTTP parsing, SQLite and optional Playwright for explicitly permitted rendered pages.
- Before starting: A small authorized URL set, reviewed selectors or field schema and a user-approved crawl frequency; no proxy-evasion machinery.
Use these project rules and optional skill references alongside the prompt. Review each skill before adding it to your agent; the AGENTS.md export includes the same guidance.
Project rule — domain: Store SourceContract, ExtractionVersion, RowKey, FieldObservation and ValidationFailure; required-field failures quarantine rows instead of coercing missing prices to zero.
Project rule — scope and recovery: Deliver one vertical dataset with documented coverage. Do not claim enterprise source maintenance, arbitrary websites or access through anti-bot restrictions.
Project rule — acceptance: A source changes currency formatting and pagination repeats a page; deduplicate row keys, retain raw price text and block comparison until parsing is reviewed.
Project rule — delivery: document real setup commands and permissions; do not claim a build, accuracy level, performance result or security certification that has not been demonstrated.
Recommended skill: modern-python — structure the Python worker or explicitly optional read-only utility with pinned dependencies, typed boundaries and clear failure handling. Follow the maintainer's installation instructions and match its requirements to the chosen runtime.
Recommended skill: agent-browser — inspect the approved browser workflow and reproduce permitted page interactions; the CLI/browser runtime is a separate prerequisite. Follow the maintainer's installation instructions and match its requirements to the chosen runtime.
Implementation plan
Phase 1
Pin the working slice and create its example input: Extract a recurring product/pricing dataset from a small approved source set with field schemas, pagination and a reviewable change report. Confirm setup: A small authorized URL set, reviewed selectors or field schema and a user-approved crawl frequency; no proxy-evasion machinery.
Phase 2
Implement persistence and write-time invariants before decorating the UI: Store SourceContract, ExtractionVersion, RowKey, FieldObservation and ValidationFailure; required-field failures quarantine rows instead of coercing missing prices to zero.
Phase 3
Connect the working view to real saved state. Bound hosts, redirects, page count, body size and timeout. Reject private-network destinations throughout redirects, respect access restrictions and backoff, and distinguish extraction failure from a missing field.
Phase 4
Expose the app-specific limits and recovery path in context: Deliver one vertical dataset with documented coverage. Do not claim enterprise source maintenance, arbitrary websites or access through anti-bot restrictions.
Phase 5
Walk through this concrete acceptance case and preserve its exported evidence: A source changes currency formatting and pagination repeats a page; deduplicate row keys, retain raw price text and block comparison until parsing is reviewed. Finish the README and backup/restore instructions; report unfinished capabilities explicitly.
Build the following focused alternative to Import.io. This is a deliberately limited personal or small-team substitute, not parity with the paid service. WORKING SLICE Extract a recurring product/pricing dataset from a small approved source set with field schemas, pagination and a reviewable change report. SETUP AND ARCHITECTURE Use Python, HTTP parsing, SQLite and optional Playwright for explicitly permitted rendered pages. Prerequisites: A small authorized URL set, reviewed selectors or field schema and a user-approved crawl frequency; no proxy-evasion machinery. Before integrating anything, record actual versions and permissions, plus model files or provider limits only where used, in the README; make unavailable dependencies visible rather than simulating success. DOMAIN MODEL AND INVARIANTS Store SourceContract, ExtractionVersion, RowKey, FieldObservation and ValidationFailure; required-field failures quarantine rows instead of coercing missing prices to zero. IMPLEMENTATION CONTRACT Bound hosts, redirects, page count, body size and timeout. Reject private-network destinations throughout redirects, respect access restrictions and backoff, and distinguish extraction failure from a missing field. Provide an input/setup view, the main work view, and a review/export view appropriate to this workflow. Preserve the last saved state if a job or save fails. Include empty, loading, permission-denied, partial and retryable-error states. Log identifiers and error categories without secret values or unnecessary private content. APP-SPECIFIC BOUNDARY AND RECOVERY Deliver one vertical dataset with documented coverage. Do not claim enterprise source maintenance, arbitrary websites or access through anti-bot restrictions. ACCEPTANCE SCENARIO A source changes currency formatting and pagination repeats a page; deduplicate row keys, retain raw price text and block comparison until parsing is reviewed. Also reopen the app after an interrupted operation, confirm the saved record/export remains inspectable, and document the recovery action. These are implementation acceptance requirements, not a claim that this guide has been tested. DELIVERY Deliver a runnable repository with migrations or project-format versioning, a non-sensitive example, environment/permission setup, the exact manual acceptance steps, and a backup/export-and-restore walkthrough. Implement the working slice before optional integrations; list any deferred paid-product capabilities honestly. Do not add capabilities outside the working slice just to resemble the original product. PROJECT RULES FOR AGENTS.md Keep the domain invariants above executable at the write boundary. Propose scope changes before adding providers or permissions. Never fabricate source evidence, publish results, identity matches or successful delivery. Preserve user originals and require an explicit confirmation for destructive changes or external publication.
$ open in your agent (prompt prefilled, you press enter), copy the prompt or copy or download AGENTS.md
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Import.io pricing
| plan | monthly | annual (per mo) | what you get |
|---|---|---|---|
| standard | $249 | $199 | 50,000 successful queries/month; $7 per additional 1,000 successful queries.Annual rate is the effective monthly price on a yearly commitment. |
| professional | $499 | $399 | 200,000 successful queries/month; $3.50 per additional 1,000 successful queries.Annual rate is the effective monthly price on a yearly commitment. |
| advanced | $899 | $699 | 500,000 successful queries/month; $2.50 per additional 1,000 successful queries.Annual rate is the effective monthly price on a yearly commitment. |
| managed web data | — | — | Custom volume above 500,000 successful queries/month; managed extraction and delivery.Quote required. |
| aperture pricing intelligence | — | — | Custom product, competitor and pricing-intelligence scope; numeric limits not publicly listed.Quote required. |
free tierno permanent free tier; 30-day trial includes 5,000 successful queries, requires no card, and hard-stops at the cap
billingmonthly + annual; annual commitment is about 20% lower than monthly
hidden costsSuccessful-query overages are automatic and tiered at $7, $3.50 or $2.50 per 1,000; managed services and custom delivery are separately quoted.
pricing sources checked 2026-08-11 · pricing source ↗
Questions about Import.io
Can you build your own Import.io with AI?
Partly. The visible enterprise web data loop is buildable, but a credible replacement needs more than the first screen. Import.io earns its keep through connectors, auth, reliability, so expect a weekend or multi-day build and a narrower personal scope.
What does the Import.io build prompt cover?
The prompt starts with this scope: Extract a recurring product/pricing dataset from a small approved source set with field schemas, pagination and a reviewable change report. Full-product capabilities excluded from the comparison include: hundreds of maintained connectors; OAuth app verification; durable execution at scale. Follow the implementation plan and its prerequisites before expanding the build.
How do I use the prompt, AGENTS.md and agent skills?
Start with the Import.io prerequisites and stack, then copy the prompt into your coding agent. Save the project rules as AGENTS.md in the project root. Linked skills are optional packages or source instructions for specific tasks; review their current contents and install only those matching the chosen stack. A skill does not supply API credentials or verify the finished app.
How long will this Import.io project take?
The catalogue estimate is weekend to multi-day for the limited scope. Setup, integration approvals, debugging, deployment and ongoing maintenance can add time. This is an estimate, not a delivery guarantee.
What would I give up by replacing Import.io?
hundreds of maintained connectors; OAuth app verification; durable execution at scale; schema drift handling and enterprise controls. Import.io: One automation is easy. Subscribers pay for maintained integrations, credentials, retries, observability, and someone else owning breakage.
What can I use instead of building Import.io?
The prior-art section lists Activepieces, n8n as starting points. Review their current scope, license and maintenance before adopting one.