Can AI replace FullStory?
A consolation build is possible, but the paid product's decisive value sits outside a solo rebuild. For FullStory, collect explicit product events and targeted debug snapshots with strong privacy controls. The hard boundary is high-fidelity replay, privacy redaction, indexing, search, storage, and compliance, plus data pipeline reliability and analytical depth.
01What it costs
Checked Aug 12, 2026 · source: fullstory.com.
| Plan | Monthly | Billed yearly | What you get |
|---|---|---|---|
| FullstoryFree | Free | Free | 30,000 sessions/month, 10 users, 12 months analytics retention, 12 months session-replay retention, and 5,000 server-side events/month |
| Business | — | — | Contracted session volume; 500,000 server-side events/month included |
| Advanced | — | — | Contracted session volume; 500,000 server-side events/month included |
| Enterprise | — | — | Contracted session volume; 500,000 server-side events/month included |
Hidden costs: Mobile, Multi-Org Management, Advantage Subscription, StoryAI, Guides and Surveys, Warehouse, Activation, and professional services are separately priced; capture pauses when a session limit is reached unless capacity is increased.
02Could AI build it for you?
The core job: Collect explicit first-party product events and targeted debug snapshots with strong privacy controls, 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 Business plan and a single-product first-party analytics DIY substitute. Recheck price before merge.
03What you'd give up
- high-fidelity replay, privacy redaction, indexing, search, storage, and compliance
- identity stitching
- session replay
- warehouse connectors
- high-volume global ingestion and support
People still pay for FullStory 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
Session replay with console, network and error context; the server bill and YAML are yours.
openreplay.com →Events, replay and privacy controls on a generous free allowance, without FullStory's enterprise gravity.
posthog.com →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 FullStory in an empty repository. Use Next.js 15, TypeScript, ClickHouse, PostgreSQL, and Docker Compose; do not offer alternative stacks. The core loop is: collect explicit first-party product events and targeted debug snapshots with strong privacy controls, 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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