CRM and sales decision
Prospectli
A competent developer can build a useful, smaller replacement (profile scraping + LLM briefs) in a few weeks, but reproducing the production polish, scale, and any proprietary integrations of the paid SaaS is nontrivial.
Visit website↗Built by Daniel Sinewe, who ships 5 products in this index
Not priced
No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.
$100one-off90 h to build
$100/mo6 h/mo upkeep
No published price to break even against.
Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All Prospectli alternatives, with the arithmetic →
What a replacement has to do
- Fetch public LinkedIn profile → extract structured facts → generate short sales brief and conversation hooks with an LLM → present brief in web UI / API
What it still won’t have
- Built-in proprietary LinkedIn integrations or enterprise connectors
- Scale, reliability, and polished UX of a paid product
- Any proprietary training data or vendor-tuned models
- Legal/terms-of-service risk handling and compliance assurances
What remains hard
- Product polish and ongoing maintenance
First-year cost
No published price
Prospectli does not publish a price we could read, so there is nothing to compare against. What building costs is below.
Money you would actually spend
Time you would spend
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What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a minimal self-hostable Prospectli replacement using Node.js (Express), Postgres, and React. Core features in scope: (1) an HTTP scraper service that fetches and rate-limits public LinkedIn profile pages and stores raw HTML, (2) an HTML parser that extracts structured fields (name, headline, current company, locations, education, skills, recent posts), (3) an LLM integration module (OpenAI-compatible) with prompt templates that generates a one-paragraph prospect summary, 3 conversation hooks, and 2 outreach openers, (4) a REST API and React SPA to view/search profiles and display generated briefs, and (5) simple user auth and job queue for generation tasks. Out of scope: browser extensions, LinkedIn private API integration, team billing, and enterprise SSO. Include retries, exponential backoff, rate-limit backoff, input validation, server-side tests for parsers and API endpoints, and end-to-end tests for the UI flows.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 3 cited sources+3
- 3/3 assessment runs agreed+4
- Evidence score64
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Cited sources · 3
Every page the run actually retrieved.
- official productProspectli | AI LinkedIn Prospect Research for Sales Teams
- open sourceRivalSearchMCP (candidate prior art)
- open sourcewacrm (candidate prior art)
Integrity checks
What held up, and what did not.
