Can AI replace Gojiberry AI?

01What it costs

Checked Aug 10, 2026 · source: gojiberry.ai.

Hidden costs: No numeric usage caps, seat limits or overages were published on the crawled page.

02Could AI build it for you?

The core job: Poll watched competitor pages and creators for likers, commenters, followers, and job changes, score each person against an ICP, enrich the ones worth contacting, draft a connection note from the exact signal that fired, and send and follow up across several of your own LinkedIn accounts until someone replies.

What a working version needs:

• a signal source: Apify actors, or a Hermes agent running the watch on a schedule
• an enrichment provider: MoltSets or Prospeo
• Unipile account with one or more LinkedIn accounts connected
• OpenAI/Anthropic API key
• Node with SQLite (better-sqlite3)

Every stage is a bought part: Apify or a Hermes agent for the signals, MoltSets or Prospeo for the enrichment, Unipile for the send. The one-shot build is the ICP scoring and the queue between them, and Unipile holding several accounts means the DIY version outsends the $99 tier.

03What you'd give up

They pay to skip the assembly and the maintenance. Gojiberry turns a website URL into a running agent in ten minutes, keeps the scrapers working when a page layout changes, and puts the signal source, the enrichment waterfall, and both channels on one bill. Rent the parts yourself and the monthly cost drops, but you own every break, you are reconciling four dashboards, and the signals only stay useful if you keep feeding the watchlist new pages and creators.

05The build prompt

Paste this into an AI coding tool (such as Claude, ChatGPT, Lovable or Replit) to build your own version.

Build me a signal-triggered LinkedIn outreach agent to replace Gojiberry AI. Requirements:

- Local Node + TypeScript service: Express dashboard on localhost:3000, better-sqlite3
  for storage, node-cron for the loop. No frontend framework.
- I define my ICP once in icp.yaml: titles, company sizes, geos, and the competitor
  LinkedIn pages and creator profiles to watch.
- Every 6 hours, pull signals with apify-client (token in .env): likers and commenters
  on watched posts, new followers, and job changes. Upsert each person into a prospects
  table with the signal, its URL, and the date it fired.
- Score each prospect 0-100 against the ICP in one LLM call (key in .env) with a
  two-line reason. Under 70 is never contacted.
- Enrich everyone above 70 through one provider, MoltSets or Prospeo · pick whichever
  ships a Node client, and cache by profile URL so I never pay twice for the same person.
- Draft a connection note under 300 characters plus two follow-ups, written from the
  profile and the exact signal that fired.
- Send through unipile-node-sdk. Connect several LinkedIn accounts and round-robin
  across them at 20 invites and 40 messages per account per day, randomized gaps in
  business hours, invite first and follow-ups only after acceptance. Poll replies every
  15 minutes and stop the sequence the moment one lands.
- Drafts wait in an approval queue until I click Send · a --auto flag skips it. The
  dashboard lists prospect, signal, score, sender account, and thread. No accounts, no
  telemetry, everything on my machine except the Apify, enrichment, Unipile, and LLM
  calls.
- Out of scope: email sequences and a hosted control plane. Do not scrape LinkedIn
  directly, every LinkedIn action goes through Unipile.
- README: the Apify actors used, how to connect each LinkedIn account in Unipile, the
  .env keys, and a warning that per-account limits are real, so keep the caps low for
  the first two weeks.

06Open-source starting points

• Hermes Agent: self-hosted agent that can run the signal watch on a schedule instead of a cron service you write
• n8n: self-hostable workflow automation, the usual no-code way to wire signals to outreach
• Mautic: open-source marketing automation with contacts, campaigns, sequences, and suppression