Can AI replace Heap?
A consolation build is possible, but the paid product's decisive value sits outside a solo rebuild. For Heap, instrument explicit first-party events and avoid automatic capture of unrelated user behavior. The hard boundary is automatic capture engine, identity graph, data science, governance, and enterprise operations, plus data pipeline reliability and analytical depth.
01What it costs
Checked Aug 12, 2026 · source: heap.io.
| Plan | Monthly | Billed yearly | What you get |
|---|---|---|---|
| Free | Free | Free | 10,000 sessions/month, 6 months data history, and 1 project/environment |
| Growth | — | — | Session-based usage estimate after installing the snippet; 12 months data history and 1 project/environment |
| Pro | — | — | Custom session volume, 1 year data history, and 3 projects/environments |
| Premier | — | — | Custom session volume, 1 year data history, and unlimited projects/environments |
Hidden costs: Session Replay, Heatmaps, Error Analysis, Heap Activate, Heap Connect, extra data-history years, and extra Pro projects are add-ons; server-side events consume capacity at 30 events = 1 session after the included contractual allowance.
02Could AI build it for you?
The core job: Instrument explicit privacy-conscious first-party events, avoid automatic capture of unrelated user behavior, answer a small set of product questions, and retain raw data under the owner's control.
What a working version needs:
- Docker
- ClickHouse
- PostgreSQL
- public HTTPS collector endpoint
- site script access
Editorial comparison targets the Pro plan and a single-product first-party analytics DIY substitute. Recheck price before merge.
03What you'd give up
- automatic capture engine, identity graph, data science, governance, and enterprise operations
- identity stitching
- session replay
- warehouse connectors
- high-volume global ingestion and support
People still pay for Heap because teams pay because analytics must keep collecting and remain trustworthy while the product changes underneath it. The recurring cost buys event schemas, bot filtering, identity, late data, retention, query cost, privacy, backups, and always-on ingestion, not just the visible interface.
04Free and cheaper alternatives
A transparent event stream with funnels and retention, free up to a million monthly events.
Versus paying: It requires deliberate event instrumentation and cannot recreate Heap's retroactive analysis of automatically captured interactions.
mixpanel.com →Event analytics and user timelines without automatic snooping; ClickHouse administration is the trade.
Versus paying: It depends on explicit events and does not provide Heap's automatic capture history for retroactive questions.
openpanel.dev →Explicit events, funnels and retention without being forced to autocapture the rest of a person's life.
Versus paying: It can autocapture, but its retroactive data engine and schema-governance workflow are less polished than Heap's.
posthog.com →Small, explicit event analytics with funnels and retention, hosted on infrastructure you control.
Versus paying: It is lightweight explicit-event analytics with no equivalent to Heap's automatic capture and retroactive history.
umami.is →05The build prompt
Paste this into an AI coding tool (such as Claude, ChatGPT, Lovable or Replit) to build your own version. Read the verdict first: this one is hard to get right.
Build a closest honest personal substitute for Heap in an empty repository. Use Next.js 15, TypeScript, ClickHouse, PostgreSQL, and Docker Compose; do not offer alternative stacks. The core loop is: instrument explicit privacy-conscious first-party events, avoid automatic capture of unrelated user behavior, answer a small set of product questions, and retain raw data under the owner's control. Make the first run work locally with one documented command. Store all user data locally by default and make export straightforward. Put secrets in .env, ship .env.example, and never commit credentials. Ship a lightweight browser SDK for page views and explicit custom events. Create projects, API keys, environments, event names, and a documented event schema. Ingest idempotently, filter obvious bots, truncate IP data, and avoid fingerprinting. Build dashboards for visitors, sessions, funnels, retention, sources, pages, and events. Expose filters by date, environment, device, country, referrer, and selected properties. Add retention controls, raw-event export, deletion, health checks, and backup instructions. Include clear empty, loading, success, and recoverable error states. Add input validation, safe filenames, and graceful handling of unavailable APIs. Write focused tests for the core transformation and one end-to-end happy path. Create a README with setup, architecture, permissions, data location, and backup steps. Do not add accounts, billing, telemetry, analytics, or a hosted control plane. Do not claim to reproduce proprietary data, network liquidity, regulated access, or frontier infrastructure. Deliberately leave out cross-site identity graphs. Deliberately leave out session replay and automatic DOM capture. Deliberately leave out warehouse-scale reverse ETL and enterprise governance. Finish by running the tests and listing the exact commands used.
06Open-source starting points
- Umami: Popular open-source privacy-focused web analytics platform.
App prices, verdicts, alternatives and build prompts are adapted from Can I Vibecode It? (MIT License, © 2026 Rob Hallam). Each price shows the date it was checked and its source. Prices change; confirm on the vendor's site before you decide.
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